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Company Description At Docplanner Group, we’re on a mission to help people live longer, healthier lives. As the world’s largest healthcare platform, each month, we connect 24 million patients with...

Gopuff delivers everyday essentials in minutes from our own network of micro-fulfillment centers. Every session, a customer sees a small, fast-changing assortment that depends on where they are, what’s in...

Excella is a transformative technology firm that helps organizations unlock new possibilities. We believe the key to helping clients challenge the status quo and reach new heights lies in our talented people. That’s why we’re committed to developing talent and providing opportunities for career growth at every stage. Join our collaborative team dedicated to solving complex problems with sustainable solutions while building your future as a leader. At Excella, you’re empowered to make lasting impact, turning today’s challenges into tomorrow’s mission successes.

• Workplace locations look different for everyone. Excellians are a distributed workforce and whether you’re working from your home office or a client site, we support a flexible work/life integration regardless of your location.
• We offer top of industry medical, dental, and vision benefits with multiple options to choose from such as an employer-contributed health savings account, infertility coverage, and orthodontia so you can select the plan that works best for you.
• Regardless of what stage of life you’re in, Excella wants to support you. We provide 8 weeks of Parental Leave, discounted pet insurance, and a Care.com membership with 3 back-up emergency child or elder care days annually – all available to you on your first day.
• Starting day one, every employee is bonus eligible and receives 15 days of paid vacation, 6 federal holidays, and 4 floating holidays.
• Doing your best work means having the best tools! Excella’s TechEleX program provides you with multiple options to suit your technology needs. Choose between a variety of Mac or PC devices, and to ensure your hardware remains current, at the end of a 3-year period Excella will replace your existing computer with a new model from the program. Plus, we’ll even give you the original device to keep for your personal use!
• With Excella’s Annual Internet Reimbursement benefit, all employees receive an additional $25 per month to help offset the cost of internet access. This initiative reflects our commitment to supporting you in staying connected and productive, no matter where you work.
• We’ll invest in your career by providing 3 days of paid professional development every year, including an allowance for registration fees to attend classes, conferences, or obtain professional certifications.
• We encourage mindfulness and overall well-being through employee wellness events, a HeadSpace membership, as well as access to TalkSpace and mental health coverage through our medical plans.

Overview

We are seeking a seasoned Lead Data Analyst who will not only deliver high-quality data analysis and insights but also mentor and guide junior analysts within the team. This role requires a balance of hands-on technical expertise and leadership skills to drive data-driven decision-making processes across our client engagements. The Lead Data Analyst will be responsible for ensuring data integrity, optimizing data models, and supporting cross-functional teams with critical insights.

Responsibilities

• Lead the analysis and interpretation of data to drive strategic business decisions.

• Serve as a mentor and coach to junior data analysts, fostering their professional development.

• Partner with stakeholders to define data-driven solutions that align with business objectives.

• Design and implement robust data models and architecture to support business needs.

• Develop advanced SQL queries to extract, transform, and analyze data efficiently.

• Oversee the creation and optimization of dashboards, reports, and data visualizations.

• Ensure best practices in data governance, quality assurance, and security compliance.

• Drive the adoption of new data analysis tools and methodologies.

• Collaborate with data engineers and data scientists to improve data pipelines and accessibility.

• Communicate complex data insights to executive stakeholders in a clear and actionable manner.

• Lead Agile data analysis initiatives, ensuring alignment with overall business strategy.

Qualifications

• 6+ years of experience in data analysis or related fields.

• Expert SQL skills, including query optimization and data transformation.

• Extensive experience with Data Visualization tools such as Tableau or Power BI.

• Strong understanding of cloud analytics products such as Google Cloud, AWS, or Microsoft Azure.

• Proven experience applying statistical techniques to drive business insights.

• Exceptional problem-solving skills and ability to manage ambiguity.

• Strong verbal and written communication skills; able to engage with senior stakeholders.

• Experience leading teams and mentoring junior analysts.

• Hands-on experience with Agile methodologies and backlog management tools (JIRA, Confluence, etc.).

• Ability to develop and present executive-level data reports and recommendations.

• Proficiency in Python or R for data analysis is a plus.

This range represents the minimum and maximum base salary that Excella reasonably and in good faith expects to pay for this role. Actual compensation within the range will depend on factors such as skills, experience, training, certifications, and organizational needs. It is not typical for an individual to be hired at or near the top or bottom of the range.

Your pay also includes the opportunity for an annual bonus in addition to the base salary. This variable pay opportunity is dependent upon the attainment of shared firmwide goals and objectives as determined by Excella’s Executive Team. Certain eligibility and pro-ration rules apply.

Should your experience and knowledge qualify you for a different position or title within Excella, we may consider you for positions that better align with your qualifications. In that case, we will provide the range for those positions as well.

Pay Range

$125,000—$182,000 USD

Excella is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected veteran status, age, or any other characteristic protected by law. Excella is committed to providing access, equal opportunity, and reasonable accommodation for individuals with disabilities in employment, its services, programs, and activities. To request reasonable accommodation to participate in the job application or interview process, contact Recruiting@excella.com or 703-840-8600.

KNOW YOUR RIGHTS

WHO ARE WE? Launch Potato is the discovery and conversion company. We reach tens of millions of people every month through our brands, including FinanceBuzz, All About Cookies, and OnlyInYourState....

WHO ARE WE? Launch Potato is the discovery and conversion company. We reach tens of millions of people every month through our brands, including FinanceBuzz, All About Cookies, and OnlyInYourState....

Headquarters: CRI - Remote

From Fivetran’s founding until now, our mission has remained the same: to make access to data as simple and reliable as electricity. With Fivetran, customer data arrives in their warehouses, canonical and ready to query, with no engineering or maintenance required. We’re proud that more organizations continue to leverage our technology every day to become truly data-driven.

About the Role

We are looking for a Staff Compensation & Data Analyst (IC4) to serve as the subject matter expert at the intersection of quantitative analysis, compensation strategy, HR technology, and AI-assisted analytics. In this role, you will lead the architecture, modeling, and execution of our global compensation programs while leveraging modern AI platforms and scalable data pipelines.

As a Staff level technical authority, you will drive business-critical compensation initiatives—from merit cycles and pay modeling to global equity strategy. You will partner with Finance, Legal, and Stock Administration on equity program design and governance, collaborate closely with Systems Engineering on Workday Compensation design and testing, utilize Carta for equity analytics, and leverage enterprise Generative AI platforms (Claude, ChatGPT) to accelerate data synthesis, narrative reporting, and predictive analytics.

This is a full-time remote position based in Costa Rica. 

What You’ll Do 

Strategic Compensation Analytics & AI-Assisted Modeling

• Architect Compensation Models: Build and maintain complex models for salary band creation, market pricing, geographic differentials, and merit/promotion budget allocation using quantitative techniques and advanced spreadsheet/coding frameworks.
• AI-Augmented Data Analytics: Leverage enterprise AI platforms (e.g., Claude, ChatGPT) to conduct exploratory analysis on large workforce datasets, synthesize compensation survey benchmarks, evaluate market trends, and automate repetitive data transformation workflows.
• Executive & Incentive Pay: Partner with leadership to model executive total compensation, short-term incentive (STI) performance metrics, and long-term incentive (LTI) grant strategies, utilizing AI tools to generate executive-level narrative summaries and scenario analyses.

Strategic Equity Strategy & Global Program Design

• Global Equity Design & Modeling: Partner with stakeholders to design and model strategic global equity frameworks,including refresh plan design, grant guidelines, vesting schedules, and budget allocations.
• Stock Administration Partnership: Work in tandem with Stock Administration to establish seamless workflows for equity grant approvals, board consent materials, vest schedules, and data reconciliation between equity systems and core HRIS.
• Equity Systems & Analytics (Carta): Utilize Carta and internal analytics tools to model wealth creation scenarios and executive equity usage to inform strategic compensation decisions.

Workday Partnership & Data Infrastructure

• Workday Compensation Design & Rollouts: Partner closely with Systems Engineering to co-design, test, administer, and execute Workday Compensation and Advanced Compensation workflows, eligibility rules, and global merit cycle rollouts.
• Data Integration & Pipeline Development: Collaborate with Systems Engineering to ensure seamless data flows between Workday, payroll systems, external survey management platforms, and analytical databases.
• Custom Reporting & BI: Design, build, and audit complex Workday custom reports, matrix reports, and calculated fields to deliver real-time total rewards insights to business leaders. Use BigQuery for querying, analyzing, and transforming large-scale datasets.

Enablement, Change Management & Training

• Program Enablement & Change Management: Apply structured change management principles to drive adoption of total rewards initiatives, merit updates, pay transparency changes, and compensation program rollouts.
• Communications & Collateral Creation: Develop comprehensive, clear, and engaging communications materials—including manager guidebooks, FAQ docs, slide decks, and video walk-throughs—tailored to various audiences.
• Stakeholder Training: Design and facilitate targeted training sessions for managers, Talent Acquisition (TA), HR Business Partners (HRBPs), and employees to build compensation and equity literacy.

Skills We’re Looking for

Experience

• 6+ years of progressive experience in compensation analysis, equity strategy, or People Analytics, with demonstrable mastery at a senior/principal individual contributor level.
• Proven track record of designing and modeling global compensation and equity programs in partnership with Finance in a fast-paced or scaling technology environment.
• Demonstrated experience with change management and driving enablement programs, including producing training collateral and leading educational workshops for cross-functional teams.

Technical & System Proficiency

• Workday Compensation: Hands-on experience working directly with Workday Core Compensation and Advanced Compensation modules is required.
• Carta & Equity Management: Hands-on experience or strong familiarity with Carta for cap table analytics, grant administration alignment, and LTI modeling is strongly preferred.
• AI Platforms & Prompt Engineering: Experience applying Large Language Model (LLM) tools such as Claude, ChatGPT, or Microsoft Copilot to data analysis, code generation (SQL/Python/Excel formulas), or report generation is strongly preferred.
• Advanced Analytics & BI: Advanced proficiency in Excel, Google Suite (VBA/macros, dynamic arrays, complex formulas) is required. Experience with BI and BigQuery tools for data modeling is a strong plus.

Core Competencies

• Cross-Functional & Executive Alignment: Exceptional ability to build strong cross-functional partnerships across Finance, Legal, Stock Admin, and Systems Engineering to deliver complex total rewards solutions.
• Quantitative Mastery: Deep familiarity with statistical techniques (e.g., regression analysis, distribution metrics) applied to compensation and equity datasets.
• Business & Legal Acumen: Solid understanding of core compensation and equity design concepts. 

Preferred Education & Certifications

• Bachelor’s or Master’s degree in Data Analytics, Finance, Human Resources, or a related field.
• CCP (Certified Compensation Professional) is a plus.
  
  

 

#LI-Remote #LI-MM1

 

Perks and Benefits

• 100% employer-paid medical insurance*
• Generous paid time away from work, including paid vacation or flexible/unlimited vacation depending on role and country, plus paid sick time, inclusive parental leave, paid holidays, including a year-end Global Week of Rest, and volunteer days off.
• RSU stock grants*
• Professional development and training opportunities
• Company virtual happy hours, free food, and fun team-building activities
• Monthly cell phone stipend
• Access to an innovative mental health support platform that offers personalized care and resources in areas such as: therapy, coaching, and self-guided mindfulness exercises for all covered employees and their covered dependents.

*May vary by country and worker type - please reach out to your recruiter for more information

Click here to learn more about Fivetran's Benefits by Region.

We’re honored to be valued at over $5.6 billion, but more importantly, we’re proud of our core values of Get Stuck In, Do the Right Thing, and One Team, One Dream. Read about us in Forbes.     

Fivetran brings together high-quality talent across the globe to make data access as easy and reliable as electricity for our customers. We value and recognize that our customers benefit from having innovative teams made of people from many backgrounds, experiences, and identities. Fivetran promotes diversity, equity, inclusion & belonging through attracting, recruiting, developing, and retaining a diverse workforce, not only because it is the right thing to do, but because it helps us build a world-class company to better serve our customers, our people and our communities.

To learn more about Fivetran’s culture and what it’s like to be part of the team, click here and enjoy our video.

To learn more about our candidate privacy policy, you can read our statement here.

We are committed to ensuring that all candidates have an equal opportunity to participate in our interview process. If you require accommodations at any stage of the process due to a disability, medical condition, or any other circumstance, please don't hesitate to submit your request by filling out this form. We will work with you to provide reasonable accommodations to facilitate your participation and ensure a fair and accessible interview experience. Your request and any information provided will be kept confidential and will not impact your candidacy. We look forward to hearing from you and accommodating your needs to the best of our ability.

To apply: https://weworkremotely.com/remote-jobs/fivetran-compensation-analytics-partner

About Tripadvisor The Tripadvisor Group connects people to experiences worth sharing, and aims to be the world’s most trusted source for travel and experiences. We leverage our brands, technology, and...

Data-AI LeadAbout Us OurRitual is a fast-growing digital platform reshaping how relationship therapy works.

At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most.

We are seeking a highly motivated and analytical individual to join our Growth Analytics International team. This team plays a crucial role in conducting research, monitoring performance, and running experiments to develop exceptional products for both consumers and merchants while driving long-term growth for the business. As Affirm continues expanding into new international markets, this role will be instrumental in establishing the operational analytics framework for new launches, beginning with Australia and expanding into future international markets. The ideal candidate will possess strong analytical and problem-solving abilities, a collaborative mindset, an eagerness to learn, and the patience to tackle complex challenges.

Our team takes an end-to-end business analytics perspective, partnering across the organization to develop recommendations and solutions that enable the business to successfully execute its growth and profitability strategies. This role requires someone who can combine analytical rigor with business acumen to influence decisions and drive measurable outcomes.

What you’ll do

• Establish and evolve the operational analytics framework for new international markets, ensuring scalable measurement, reporting, and decision-making capabilities as we expand globally.
• Operate with a business owner mindset by proactively identifying opportunities through analysis and product sense to enhance user experience, growth, and profitability.
• Own business problems from end to end by translating analytical insights into recommendations and optimization strategies that support business growth, profitability, and operational excellence.
• Take ownership of the end-to-end analytics process: define success metrics, generate insights and hypotheses, track performance, and create intuitive dashboards and reports that can be easily shared across the organization. Develop scalable analytics solutions and data models.
• Tackle ambiguous problems by identifying the core hypotheses and designing actionable experiments to validate product-market fit and economic viability.
• Translate analytical findings into clear and compelling narratives and business cases for leadership to inform decision-making.
• Spearhead weekly cross-functional metric reviews, collaborating with partners to conduct deep dives into significant metric shifts and suggest actionable steps.
• Partner effectively across Product, Risk, Finance, Commercial, and Operations to align strategies and execute against business objectives.
• Foster strong cross-functional relationships and establish yourself as a trusted advisor to team members.
• Mentor and guide junior analysts to deliver high-impact work that drives business results.

What we look for:

• Passion to redefine the lending and financial industry for the better.
• Strong understanding of the consumer lending and credit industry, including lending economics, portfolio performance, and credit metrics. Experience supporting international lending markets, particularly Europe and/or APAC, is highly desirable.
• Demonstrated ability to balance growth objectives with profitability and develop data-driven growth strategies.
• Bachelor’s or Master’s degree in a quantitatively rigorous subject area such as statistics, mathematics, finance, or economics.
• 5+ years of proven success in a cross-functional analytical role.
• Practical and theoretical knowledge of A/B testing.
• Experience with SQL and performing statistical analysis using Python.
• Experience simultaneously balancing multiple workstreams and prioritizing an analytics roadmap.
• Demonstrated curiosity and a growth mindset, with hands-on experience using AI-powered tools such as Cursor, Claude, or similar assistants to accelerate analysis, automate workflows, enhance problem-solving, and advocate for AI adoption across analytical workflows.
• Strong interpersonal and communication skills, with the ability to influence both technical and non-technical audiences.
• Comfortable partnering across multiple cross-functional teams, particularly Product, Risk, Commercial, Finance, and Operations.
• Ability to think creatively and critically while thriving in a fast-paced, dynamic, and often ambiguous work environment.
• Willingness to go out of your way to help teammates, with humility and a team-first mindset.
• Previous experience mentoring and guiding junior analysts.

Compensation & Benefits

Base Pay Grade - M

Equity Grade - 5

Employees new to Affirm typically come in at the start of the pay range. Affirm focuses on providing a simple and transparent pay structure which is based on a variety of factors, including location, experience and job-related skills.

Base pay is part of a total compensation package that may include monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents). In addition, the employees may be eligible for equity rewards offered by Affirm Holdings, Inc. (parent company).

CAN base pay range per year: $145,000 - $205,000

#LI-Remote

Remote-first with flexibility built in Affirm is proud to be a remote-first company. Most roles can be done from almost anywhere within the country of employment. Some positions may occasionally require in-person work at an Affirm office, and a few are office-based due to the nature of the work. All new hires will be invited to attend an in-person onboarding experience.

Benefits designed for you Our benefits reflect our commitment to care, transparency, and flexibility. Here are a few highlights:

• Health coverage at no cost: We cover 100% of premiums for employees and their dependents.
• Spending stipends: Monthly stipends support your tech setup, and the ability to choose health and wellness options that are right for you.
• Time off to recharge: Flexible time off and generous holiday calendars help you rest when you need to.
• Own a piece of what you build: Our employee stock purchase plan (ESPP) lets you buy Affirm stock at a discount.

We’re committed to providing an inclusive interview process, including accommodations for candidates with disabilities. If you need support, we’re happy to help.

For positions based in San Francisco or Los Angeles: Affirm considers qualified applicants with arrest and conviction records, as required by law.

By clicking “Submit Application,” you acknowledge that you have read Affirm’s Global Candidate Privacy Notice and consent to the use of your personal information as described.

At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most.

We are seeking a highly motivated and analytical individual to join our Growth Analytics International team. This team plays a crucial role in conducting research, monitoring performance, and running experiments to develop exceptional products for both consumers and merchants while driving long-term growth for the business. As Affirm continues expanding into new international markets, this role will be instrumental in establishing the operational analytics framework for new launches, beginning with Australia and expanding into future international markets. The ideal candidate will possess strong analytical and problem-solving abilities, a collaborative mindset, an eagerness to learn, and the patience to tackle complex challenges.

Our team takes an end-to-end business analytics perspective, partnering across the organization to develop recommendations and solutions that enable the business to successfully execute its growth and profitability strategies. This role requires someone who can combine analytical rigor with business acumen to influence decisions and drive measurable outcomes.

What you’ll do

• Establish and evolve the operational analytics framework for new international markets, ensuring scalable measurement, reporting, and decision-making capabilities as we expand globally.
• Operate with a business owner mindset by proactively identifying opportunities through analysis and product sense to enhance user experience, growth, and profitability.
• Own business problems from end to end by translating analytical insights into recommendations and optimization strategies that support business growth, profitability, and operational excellence.
• Take ownership of the end-to-end analytics process: define success metrics, generate insights and hypotheses, track performance, and create intuitive dashboards and reports that can be easily shared across the organization. Develop scalable analytics solutions and data models.
• Tackle ambiguous problems by identifying the core hypotheses and designing actionable experiments to validate product-market fit and economic viability.
• Translate analytical findings into clear and compelling narratives and business cases for leadership to inform decision-making.
• Spearhead weekly cross-functional metric reviews, collaborating with partners to conduct deep dives into significant metric shifts and suggest actionable steps.
• Partner effectively across Product, Risk, Finance, Commercial, and Operations to align strategies and execute against business objectives.
• Foster strong cross-functional relationships and establish yourself as a trusted advisor to team members.
• Mentor and guide junior analysts to deliver high-impact work that drives business results.

What we look for:

• Passion to redefine the lending and financial industry for the better.
• Strong understanding of the consumer lending and credit industry, including lending economics, portfolio performance, and credit metrics. Experience supporting international lending markets, particularly Europe and/or APAC, is highly desirable.
• Demonstrated ability to balance growth objectives with profitability and develop data-driven growth strategies.
• Bachelor’s or Master’s degree in a quantitatively rigorous subject area such as statistics, mathematics, finance, or economics.
• 5+ years of proven success in a cross-functional analytical role.
• Practical and theoretical knowledge of A/B testing.
• Experience with SQL and performing statistical analysis using Python.
• Experience simultaneously balancing multiple workstreams and prioritizing an analytics roadmap.
• Demonstrated curiosity and a growth mindset, with hands-on experience using AI-powered tools such as Cursor, Claude, or similar assistants to accelerate analysis, automate workflows, enhance problem-solving, and advocate for AI adoption across analytical workflows.
• Strong interpersonal and communication skills, with the ability to influence both technical and non-technical audiences.
• Comfortable partnering across multiple cross-functional teams, particularly Product, Risk, Commercial, Finance, and Operations.
• Ability to think creatively and critically while thriving in a fast-paced, dynamic, and often ambiguous work environment.
• Willingness to go out of your way to help teammates, with humility and a team-first mindset.
• Previous experience mentoring and guiding junior analysts.

Compensation & Benefits

Base Pay Grade - M

Equity Grade - 5

Employees new to Affirm typically come in at the start of the pay range. Affirm focuses on providing a simple and transparent pay structure which is based on a variety of factors, including location, experience and job-related skills.

Base pay is part of a total compensation package that may include monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents). In addition, the employees may be eligible for equity rewards offered by Affirm Holdings, Inc. (parent company).

CAN base pay range per year: $145,000 - $205,000

#LI-Remote

Remote-first with flexibility built in Affirm is proud to be a remote-first company. Most roles can be done from almost anywhere within the country of employment. Some positions may occasionally require in-person work at an Affirm office, and a few are office-based due to the nature of the work. All new hires will be invited to attend an in-person onboarding experience.

Benefits designed for you Our benefits reflect our commitment to care, transparency, and flexibility. Here are a few highlights:

• Health coverage at no cost: We cover 100% of premiums for employees and their dependents.
• Spending stipends: Monthly stipends support your tech setup, and the ability to choose health and wellness options that are right for you.
• Time off to recharge: Flexible time off and generous holiday calendars help you rest when you need to.
• Own a piece of what you build: Our employee stock purchase plan (ESPP) lets you buy Affirm stock at a discount.

We’re committed to providing an inclusive interview process, including accommodations for candidates with disabilities. If you need support, we’re happy to help.

For positions based in San Francisco or Los Angeles: Affirm considers qualified applicants with arrest and conviction records, as required by law.

By clicking “Submit Application,” you acknowledge that you have read Affirm’s Global Candidate Privacy Notice and consent to the use of your personal information as described.

[Quora is a privately held, “remote-first” company. This position can be performed remotely from multiple countries around the world. Please visit careers.quora.com/eligible-countries for details regarding employment eligibility by country.] About...

[Quora is a privately held, “remote-first” company. This position can be performed remotely from multiple countries around the world. Please visit careers.quora.com/eligible-countries for details regarding employment eligibility by country.] About...

To learn the Hiring Ranges for this position, please select your location from the Apply Now dropdown menu. To learn more about our Hiring Range System, please click this link....

Headquarters: Brazil
URL: http://lawnstarter.com

About LawnStarter

LawnStarter is the nation's leading on-demand marketplace for lawn care and outdoor services, with over $750M in annual bookings. We're expanding beyond lawn care to become the one-stop shop for all home services, operating across three brands (LawnStarter, Lawn Love, Home Gnome) on a single shared platform.

About Analytics at LawnStarter

We're a small, senior analytics team supporting the entire company, product, marketing, operations, and finance all run on the data we serve. The foundation is solid: a centralized Redshift data warehouse where all source data lands, modeled in dbt and orchestrated by Airflow, with Segment feeding event data in. You won't be stitching scattered sources together, the platform exists; your job is to make it trustworthy and keep it that way. We're mid-migration to Lightdash as our single BI platform, replacing Tableau and Metabase.

Here's the honest gap: everyone on the team today is an analyst. Data quality, tracking standards, and platform hygiene get done as side work, squeezed between analyses. Nobody wakes up thinking about them, which is exactly the job we're hiring for.

The Role

You'll be the first person at LawnStarter dedicated to data governance, the owner of whether our data can be trusted, and of the roadmap that makes it more trustworthy every quarter. Trust means the quality and freshness of our source data, pipelines, and reports; the definitions behind our metrics; the standards behind our Segment event tracking; the health of our Lightdash workspace; the data feeding our machine learning models; and the security of the data itself. The roadmap means sitting with product, marketing, ops, and finance to understand what the business needs from data, turning that into priorities for the platform, and sequencing the work, yours and, soon, your team's.

This is a hands-on role, every manager at LawnStarter builds, and this one is no exception. You'll start solo, with the Analytics team around you: building automation, writing checks, fixing what's broken, and putting processes in place that scale past you. Once you've landed, we open a Lead Analytics Engineer role reporting to you, you'll help choose them, and the function grows from there as scope demands.

What makes this role different:

• You're first. Governance has been everyone's side job, so what exists today is yours to reshape, keep what works, redesign what doesn't, and your standards become the company's standards.
• You own the roadmap, not a backlog. Nobody hands you requirements, you discover what the business needs from data and decide what gets built, in what order, and why.
• Whole-stack ownership. Source data to pipelines to dashboards and ML models, you own trust across the entire chain, not one slice of it.
• A live migration to shape. Lightdash is landing now. You get to set up its permissions, structure, and norms before bad habits form, instead of untangling them later.

What You'll Own

• The data roadmap - discovering what product, marketing, ops, and finance need from data, prioritizing it against platform health, and sequencing the investment. You'll present it, defend it, and re-plan it as the business moves.
• Data quality and freshness - automated monitoring across source data, pipelines, and reports; catching upstream schema and source changes before they break anything downstream; running incidents to resolution when they happen.
• Data lineage and impact analysis - a living map from production source to warehouse model to dashboard, and the process that uses it: when a production change is proposed, its downstream impact on pipelines, metrics, and reports gets assessed before it ships, not discovered after. The end-state is data contracts with engineering, so breaking changes get caught in their workflow, not ours.
• Lightdash - administration, workspace structure, permissions, and the rollout itself. Your job is to give the company self-serve autonomy while keeping the workspace tidy enough that people can find and trust what's there. Enablement is part of the deal, people follow standards they've been taught, and so is keeping queries fast and warehouse costs sane.
• The semantic layer - we just shipped it for our most critical metrics: one governed definition per metric, in code. You'll extend definition and mapping to the rest and guard the layer against uncontrolled growth as it scales.
• Event tracking governance - our governed Segment event catalog: reviewing new events against its standards, keeping it matched to what production actually sends, and evolving the guardrails (naming, property dictionary, drift detection) as tracking grows.
• AI data readiness - AI agents query our warehouse every day through Brain, our internal AI toolkit. You'll govern what data AI tools can access and keep the warehouse AI-legible: documented, consistent, and safe for an agent to query and get the right answer.
• Data security and privacy - access controls, PII handling and retention under US state privacy laws, and periodic reviews of who, and which AI tools, can see what.
• The governance system itself - the documentation, ownership models, and review loops that keep all of the above running without heroics.

Problems to Solve

Turn business needs into a data roadmap Every area of the company wants something from data, and today those asks reach the Analytics team as a stream of interruptions. You'll build the intake and prioritization that turns them into a roadmap , one that balances stakeholder needs against platform health, survives contact with a changing business, and that your stakeholders can see themselves in. The hard part: saying "not yet" to important people, with a reason they respect.

Make the Lightdash migration a step-change, not a re-platforming We're replacing Tableau and Metabase with Lightdash. Done poorly, we trade two messy tools for one messy tool. You'll design the structure, spaces, permissions, certification, naming, that lets stakeholders self-serve at the speed the company needs without creating an uncontrolled dashboard-growth nightmare. The hard part: autonomy and tidiness pull in opposite directions, and you have to deliver both.

Finish and defend the semantic layer We just shipped our semantic layer for our most critical metrics, one governed definition per metric, so "two dashboards, two numbers" can't happen. The unglamorous truth: a long tail of metrics still needs definition and mapping, and a semantic layer only stays trustworthy if someone curbs its growth. You'll own both, extending coverage and keeping one-metric-one-definition true as the layer scales.

Tame event-tracking entropy Segment events power our funnels and product analytics, and they're implemented by many engineers across many teams. The guardrails exist, a governed event catalog with naming standards, a property dictionary, a review lifecycle, and automated drift detection against production. What's missing is a dedicated owner: someone who holds every new event to the standard, keeps the catalog matched to what production actually sends, and evolves the guardrails as tracking grows. Without that, entropy wins, events drift and silently degrade when features change.

Get ahead of breakage instead of chasing it Today, when production data changes upstream, we too often find out when a pipeline breaks or a stakeholder flags a wrong number. You won't start from zero, an AI-powered Analytics Engineer agent already runs freshness monitoring, metric anomaly detection, and dbt-based lineage checks, but it doesn't yet run at the scale or coverage we need. You'll take detection from partial to comprehensive, extend lineage beyond dbt (Segment events and Lightdash need stitching in), and wire it into engineering's change review, so a proposed production change comes with a downstream impact assessment instead of a postmortem. The end-state is data contracts: breaking changes caught in engineering's workflow, not ours.

What Success Looks Like (Year 1)

• Zero pipeline incidents from unannounced source-data changes - lineage and automation catch them before they break anything downstream, and production changes ship with an impact assessment instead of a postmortem.
• Zero freshness incidents - stakeholders never open a stale dashboard.
• Every area of the business manages on official, well-maintained metrics and dashboards - product, marketing, ops, and finance self-serve in Lightdash against a fully mapped semantic layer; Tableau and Metabase are retired; arguments about whose number is right don't happen. Not because you built the dashboards - because you built the system that keeps them trustworthy.
• Every Segment event has an owner and a standard - new events ship compliant, and degradation gets caught automatically, not by accident.
• Governance runs as a system - documented processes that would survive you taking a month off.

Requirements

Who You Are

• Governance is your craft, not your chore. You genuinely enjoy making data systems trustworthy and tidy, you're the person who can't leave a broken naming convention alone. This is unlikely to be a good fit if you see governance as a stepping stone to "real" analytics work.
• AI-native. You use AI tools (Claude Code, Copilot, ChatGPT) daily to build quality checks, write automation, triage anomalies, and document as you go, one person covering ground that used to take a team. You also see the reverse direction: AI agents consume our data daily, and making the warehouse safe and legible for them is part of governance now. This is unlikely to be a good fit if you're skeptical of AI tools or prefer to do everything manually.
• A hands-on manager. You've been accountable for other people's output, allocating their time, owning their priorities, and you never stopped building yourself. You write the SQL, debug the Airflow DAG, and configure the permissions personally. This is unlikely to be a good fit if seniority took you away from the keyboard, or if you've never been responsible for anyone's work but your own.
• Product-minded. You start from what the business is trying to decide, not from what the pipeline does, and you can turn a vague stakeholder ask into a prioritized plan. This is unlikely to be a good fit if you need requirements handed to you, or if roadmap conversations feel like a distraction from the real work.
• Automation-first. Your instinct for any recurring check is to build a monitor, not a checklist. This is unlikely to be a good fit if your quality practice depends on manual review and discipline.
• An enforcer people actually like. You'll hold engineers and analysts you don't manage to standards, which takes clear rules, good tooling that makes compliance easy, and the spine to say no gracefully. This is unlikely to be a good fit if you avoid friction or, at the other extreme, enjoy being the department of no.

This Role Is NOT

• A big-team leadership role. You start solo and then hire a Lead Analytics Engineer who reports to you; the team grows only as scope demands. If you want to direct a large org rather than build alongside a small one, this isn't it.
• A policy or committee job. There are no governance councils to chair and no binders to produce. When something's broken, you fix it, with code, config, or a conversation.
• A BI analyst role. You won't spend your days building dashboards for stakeholders. You build the platform and guardrails that let everyone else do that well.
• A finished system to babysit. Much of this doesn't exist yet. If you want to operate a mature data platform rather than build one, you'll be frustrated here.

Tech You'll Touch

• Warehouse & pipelines - Redshift, dbt, Airflow
• Ingestion - Fivetran, plus custom Airflow pipelines
• Event tracking - Segment
• BI - Lightdash (primary), Tableau and Metabase (sunsetting)
• AI tooling - Claude Code, Codex, Brain (our internal AI toolkit), and any tool that makes you more effective or efficient
• Observability - an AI-powered Analytics Engineer agent (freshness monitoring, anomaly detection, dbt lineage) you'll scale up, plus the quality and impact tooling you'll add around it

You don't need every box checked. You need hands-on depth in the warehouse/pipeline layer and credible experience keeping a BI tool and tracking plan healthy at company scale.

Benefits

• Base salary: $75k-$120k/year
• Fully remote: This work needs deep focus, building monitors, untangling pipelines, and we trust you to manage your environment. Async collaboration is the norm.
• Flexible PTO: We focus on results. Take what you need.

LawnStarter provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, or genetics. We comply with applicable state and local laws governing nondiscrimination in employment.

To apply: https://weworkremotely.com/remote-jobs/lawnstarter-analytics-engineering-manager-data-platform-governance

Headquarters: Mexico
URL: http://lawnstarter.com

About LawnStarter

LawnStarter is the nation's leading on-demand marketplace for lawn care and outdoor services, with over $750M in annual bookings. We're expanding beyond lawn care to become the one-stop shop for all home services, operating across three brands (LawnStarter, Lawn Love, Home Gnome) on a single shared platform.

About Analytics at LawnStarter

We're a small, senior analytics team supporting the entire company, product, marketing, operations, and finance all run on the data we serve. The foundation is solid: a centralized Redshift data warehouse where all source data lands, modeled in dbt and orchestrated by Airflow, with Segment feeding event data in. You won't be stitching scattered sources together, the platform exists; your job is to make it trustworthy and keep it that way. We're mid-migration to Lightdash as our single BI platform, replacing Tableau and Metabase.

Here's the honest gap: everyone on the team today is an analyst. Data quality, tracking standards, and platform hygiene get done as side work, squeezed between analyses. Nobody wakes up thinking about them, which is exactly the job we're hiring for.

The Role

You'll be the first person at LawnStarter dedicated to data governance, the owner of whether our data can be trusted, and of the roadmap that makes it more trustworthy every quarter. Trust means the quality and freshness of our source data, pipelines, and reports; the definitions behind our metrics; the standards behind our Segment event tracking; the health of our Lightdash workspace; the data feeding our machine learning models; and the security of the data itself. The roadmap means sitting with product, marketing, ops, and finance to understand what the business needs from data, turning that into priorities for the platform, and sequencing the work, yours and, soon, your team's.

This is a hands-on role, every manager at LawnStarter builds, and this one is no exception. You'll start solo, with the Analytics team around you: building automation, writing checks, fixing what's broken, and putting processes in place that scale past you. Once you've landed, we open a Lead Analytics Engineer role reporting to you, you'll help choose them, and the function grows from there as scope demands.

What makes this role different:

• You're first. Governance has been everyone's side job, so what exists today is yours to reshape, keep what works, redesign what doesn't, and your standards become the company's standards.
• You own the roadmap, not a backlog. Nobody hands you requirements, you discover what the business needs from data and decide what gets built, in what order, and why.
• Whole-stack ownership. Source data to pipelines to dashboards and ML models, you own trust across the entire chain, not one slice of it.
• A live migration to shape. Lightdash is landing now. You get to set up its permissions, structure, and norms before bad habits form, instead of untangling them later.

What You'll Own

• The data roadmap - discovering what product, marketing, ops, and finance need from data, prioritizing it against platform health, and sequencing the investment. You'll present it, defend it, and re-plan it as the business moves.
• Data quality and freshness - automated monitoring across source data, pipelines, and reports; catching upstream schema and source changes before they break anything downstream; running incidents to resolution when they happen.
• Data lineage and impact analysis - a living map from production source to warehouse model to dashboard, and the process that uses it: when a production change is proposed, its downstream impact on pipelines, metrics, and reports gets assessed before it ships, not discovered after. The end-state is data contracts with engineering, so breaking changes get caught in their workflow, not ours.
• Lightdash - administration, workspace structure, permissions, and the rollout itself. Your job is to give the company self-serve autonomy while keeping the workspace tidy enough that people can find and trust what's there. Enablement is part of the deal, people follow standards they've been taught, and so is keeping queries fast and warehouse costs sane.
• The semantic layer - we just shipped it for our most critical metrics: one governed definition per metric, in code. You'll extend definition and mapping to the rest and guard the layer against uncontrolled growth as it scales.
• Event tracking governance - our governed Segment event catalog: reviewing new events against its standards, keeping it matched to what production actually sends, and evolving the guardrails (naming, property dictionary, drift detection) as tracking grows.
• AI data readiness - AI agents query our warehouse every day through Brain, our internal AI toolkit. You'll govern what data AI tools can access and keep the warehouse AI-legible: documented, consistent, and safe for an agent to query and get the right answer.
• Data security and privacy - access controls, PII handling and retention under US state privacy laws, and periodic reviews of who, and which AI tools, can see what.
• The governance system itself - the documentation, ownership models, and review loops that keep all of the above running without heroics.

Problems to Solve

Turn business needs into a data roadmap Every area of the company wants something from data, and today those asks reach the Analytics team as a stream of interruptions. You'll build the intake and prioritization that turns them into a roadmap , one that balances stakeholder needs against platform health, survives contact with a changing business, and that your stakeholders can see themselves in. The hard part: saying "not yet" to important people, with a reason they respect.

Make the Lightdash migration a step-change, not a re-platforming We're replacing Tableau and Metabase with Lightdash. Done poorly, we trade two messy tools for one messy tool. You'll design the structure, spaces, permissions, certification, naming, that lets stakeholders self-serve at the speed the company needs without creating an uncontrolled dashboard-growth nightmare. The hard part: autonomy and tidiness pull in opposite directions, and you have to deliver both.

Finish and defend the semantic layer We just shipped our semantic layer for our most critical metrics, one governed definition per metric, so "two dashboards, two numbers" can't happen. The unglamorous truth: a long tail of metrics still needs definition and mapping, and a semantic layer only stays trustworthy if someone curbs its growth. You'll own both, extending coverage and keeping one-metric-one-definition true as the layer scales.

Tame event-tracking entropy Segment events power our funnels and product analytics, and they're implemented by many engineers across many teams. The guardrails exist, a governed event catalog with naming standards, a property dictionary, a review lifecycle, and automated drift detection against production. What's missing is a dedicated owner: someone who holds every new event to the standard, keeps the catalog matched to what production actually sends, and evolves the guardrails as tracking grows. Without that, entropy wins, events drift and silently degrade when features change.

Get ahead of breakage instead of chasing it Today, when production data changes upstream, we too often find out when a pipeline breaks or a stakeholder flags a wrong number. You won't start from zero, an AI-powered Analytics Engineer agent already runs freshness monitoring, metric anomaly detection, and dbt-based lineage checks, but it doesn't yet run at the scale or coverage we need. You'll take detection from partial to comprehensive, extend lineage beyond dbt (Segment events and Lightdash need stitching in), and wire it into engineering's change review, so a proposed production change comes with a downstream impact assessment instead of a postmortem. The end-state is data contracts: breaking changes caught in engineering's workflow, not ours.

What Success Looks Like (Year 1)

• Zero pipeline incidents from unannounced source-data changes - lineage and automation catch them before they break anything downstream, and production changes ship with an impact assessment instead of a postmortem.
• Zero freshness incidents - stakeholders never open a stale dashboard.
• Every area of the business manages on official, well-maintained metrics and dashboards - product, marketing, ops, and finance self-serve in Lightdash against a fully mapped semantic layer; Tableau and Metabase are retired; arguments about whose number is right don't happen. Not because you built the dashboards - because you built the system that keeps them trustworthy.
• Every Segment event has an owner and a standard - new events ship compliant, and degradation gets caught automatically, not by accident.
• Governance runs as a system - documented processes that would survive you taking a month off.

Requirements

Who You Are

• Governance is your craft, not your chore. You genuinely enjoy making data systems trustworthy and tidy, you're the person who can't leave a broken naming convention alone. This is unlikely to be a good fit if you see governance as a stepping stone to "real" analytics work.
• AI-native. You use AI tools (Claude Code, Copilot, ChatGPT) daily to build quality checks, write automation, triage anomalies, and document as you go, one person covering ground that used to take a team. You also see the reverse direction: AI agents consume our data daily, and making the warehouse safe and legible for them is part of governance now. This is unlikely to be a good fit if you're skeptical of AI tools or prefer to do everything manually.
• A hands-on manager. You've been accountable for other people's output, allocating their time, owning their priorities, and you never stopped building yourself. You write the SQL, debug the Airflow DAG, and configure the permissions personally. This is unlikely to be a good fit if seniority took you away from the keyboard, or if you've never been responsible for anyone's work but your own.
• Product-minded. You start from what the business is trying to decide, not from what the pipeline does, and you can turn a vague stakeholder ask into a prioritized plan. This is unlikely to be a good fit if you need requirements handed to you, or if roadmap conversations feel like a distraction from the real work.
• Automation-first. Your instinct for any recurring check is to build a monitor, not a checklist. This is unlikely to be a good fit if your quality practice depends on manual review and discipline.
• An enforcer people actually like. You'll hold engineers and analysts you don't manage to standards, which takes clear rules, good tooling that makes compliance easy, and the spine to say no gracefully. This is unlikely to be a good fit if you avoid friction or, at the other extreme, enjoy being the department of no.

This Role Is NOT

• A big-team leadership role. You start solo and then hire a Lead Analytics Engineer who reports to you; the team grows only as scope demands. If you want to direct a large org rather than build alongside a small one, this isn't it.
• A policy or committee job. There are no governance councils to chair and no binders to produce. When something's broken, you fix it, with code, config, or a conversation.
• A BI analyst role. You won't spend your days building dashboards for stakeholders. You build the platform and guardrails that let everyone else do that well.
• A finished system to babysit. Much of this doesn't exist yet. If you want to operate a mature data platform rather than build one, you'll be frustrated here.

Tech You'll Touch

• Warehouse & pipelines - Redshift, dbt, Airflow
• Ingestion - Fivetran, plus custom Airflow pipelines
• Event tracking - Segment
• BI - Lightdash (primary), Tableau and Metabase (sunsetting)
• AI tooling - Claude Code, Codex, Brain (our internal AI toolkit), and any tool that makes you more effective or efficient
• Observability - an AI-powered Analytics Engineer agent (freshness monitoring, anomaly detection, dbt lineage) you'll scale up, plus the quality and impact tooling you'll add around it

You don't need every box checked. You need hands-on depth in the warehouse/pipeline layer and credible experience keeping a BI tool and tracking plan healthy at company scale.

Benefits

• Base salary: $75k-$120k/year
• Fully remote: This work needs deep focus, building monitors, untangling pipelines, and we trust you to manage your environment. Async collaboration is the norm.
• Flexible PTO: We focus on results. Take what you need.

LawnStarter provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, or genetics. We comply with applicable state and local laws governing nondiscrimination in employment.

To apply: https://weworkremotely.com/remote-jobs/lawnstarter-analytics-engineering-manager-data-platform-governance-1

Do you want to empower organizations to build smarter compensation strategies while ensuring fair pay for all employees?

Syndio is the leading pay governance and compensation intelligence platform. We help organizations make better pay decisions at every stage of the compensation lifecycle, from leveling and offers to promotions and merit. Our platform gives HR, compensation, and finance leaders the data and decision support they need to govern pay fairly, compliantly, and with confidence. We partner with many of the world’s most recognized and respected enterprises, helping them implement leading-edge compensation solutions with expert guidance and analyzing pay for over 10 million employees across the world.

Join us in our mission to help companies make smarter pay decisions they can trust!

About the role

We are looking for a Staff Data Scientist, Data Products to serve as a senior analytical and product partner across Syndio’s product and data-product portfolio. You will own measurement strategies for our product platform, translate usage and business data into product decisions, and help turn those signals — together with pay-equity, policy, job architecture, market, and workforce data — into customer-facing analytical products.

This is a high-autonomy, high-visibility staff role. You will lead ambiguous, cross-functional work from opportunity discovery through methodology, validation, production, and launch; partner with Product, Data Science, Engineering, Privacy, Legal, Sales, and Customer Success; and set standards for analytical rigor, interpretability, data quality, and responsible data use. The role is an individual contributor position with broad influence.

Why this job is exciting

Product Measurement & Decision Support

• Own measurement strategies for Syndi’s core user workflows — including offer endorsement, approval, and acceptance — defining events, metrics, and success criteria that guide product decisions.
• Partner with engineering to design and validate event instrumentation for new features, ensuring tracking is accurate, consistent, and privacy-safe from the start.
• Conduct deep-dive analyses into feature adoption, workflow completion, user engagement, customer outcomes, and operational patterns to surface actionable insights.
• Build and maintain production-grade dashboards and self-serve reporting in Mixpanel, BigQuery, and BI tooling that give product teams and senior leaders visibility into product health.
• Translate complex, ambiguous usage data into clear, prioritized recommendations for technical, product, and executive audiences.

Data Product Development

• Define and lead analytical strategies for new compensation and workforce data products that make Syndio more valuable, differentiated, and difficult to replicate.
• Identify high-value opportunities to combine Syndio’s aggregated and anonymized first-party data with compensation market data, job-posting and skills data, and other third-party sources.
• Develop diagnostics that measure compensation governance and execution health, including policy-versus-practice gaps, job-architecture health, governance adoption, strategic alignment, and overpayment risk.
• Lead complex initiatives from early exploration and hypothesis formation through analytical validation, productionization, commercialization, and launch.
• Evaluate whether proposed data products are analytically defensible, interpretable, commercially valuable, privacy-preserving, and responsible to use.
• Contribute to the give-to-get data strategy by identifying which product and customer signals can strengthen Syndio’s broader data assets over time.

Cross-functional Leadership & Standards

• Serve as a senior analytical partner in product discovery, sprint planning, roadmap discussions, business reviews, and product planning cycles.
• Partner with Data Science on experiment design, causal analysis, model evaluation, and measurement of model-assisted workflows.
• Work with Customer Success and Sales to connect product usage and data-product insights to customer value, health, and renewal risk.
• Establish and champion standards for event data, analytical quality, documentation, interpretability, privacy, and responsible data use.
• Provide technical and analytical leadership to other practitioners, raise data literacy across the product organization, and build self-serve capability.

About you

• 8+ years of experience in product analytics, data science, analytics engineering, or a closely related role, including substantial experience supporting software products and/or developing analytical products.
• Proficiency with AI-assisted development tools and workflows, using them to accelerate analysis, prototyping, code generation, documentation, and data-product development while validating outputs and exercising sound judgment.
• Familiarity with emerging AI and BI innovation — including natural-language interfaces, automated insights, semantic layers, and agentic workflows — and the ability to evaluate where these capabilities can improve analytical products and customer experiences.
• A track record of setting direction and leading complex, cross-functional initiatives with significant product or business impact.
• Deep proficiency in SQL and strong working proficiency with Python, R, or a comparable analytical language.
• Advanced knowledge of statistical measurement, benchmarking, experimentation, data modeling, segmentation, data quality assessment, and analytical validation.
• Experience designing event schemas, product measurement strategies, funnels, dashboards, and self-serve reporting using tools such as Mixpanel, Amplitude, Looker, Tableau, or equivalent.
• Experience combining large, imperfect datasets into analytically defensible, interpretable, and commercially valuable products or insights.
• Exceptional judgment and comfort operating in ambiguous, evolving problem spaces; able to determine when approximation is appropriate and when precision is required.
• Ability to influence senior stakeholders, communicate complex methodologies clearly, and drive alignment across technical and non-technical audiences.

Extra Credit

• Experience instrumenting or evaluating a GenAI-native product, including model-assisted workflows.
• Deep familiarity with compensation, pay equity, workforce planning, labor-market data, job architecture, skills taxonomies, or people analytics.
• Experience with compensation surveys, job-posting data, privacy-preserving analytics, or third-party data licensing and governance.
• Familiarity with GDPR/CCPA and related privacy considerations for user-level event data and aggregated or anonymized customer data.

Why you’ll love it here:

• 💰 Competitive Compensation. For this role our salary is targeted at $180,000 -$205,000 per year. Final offer amounts are determined by factors such as experience and expertise. We take a geo neutral approach to compensation within the US, meaning that we pay based on job function and level, not location.
• 🏆  Syndio Equity. So you can share in Syndio’s success.
• 🏝  Flexible Vacation Policy. We encourage our team to recharge when they need to, plus paid sick & safe time, compassion leave, and voting leave.
• Paid parental leave
• 🩺  Medical, Dental, Vision. Syndio pays 90% of employee premiums, and 50% for dependents.
• 🏥  Life Insurance & Disability. Syndio covers the full premium.
• 🏦 401(k). To help you save for your future
• Fully remote model - #LI-Remote

The interview overview

Below you’ll find an outline of the interview plan for our Staff Data Science position. Please note that this is what we expect the process to look like; we may ask you for supplemental information or require an additional step before making a final decision.

• 30 min interview with a member of our Talent Team
• 45 minute zoom interview with the Hiring Manager
• Three video interviews with several team members
• Final interviews with executive

At Syndio, we’re building a diverse team that values candor, curiosity, and community. If you share these values and are interested in joining us, we’d love to talk with you even if you don’t 100% meet the “about you” listed here. We don’t expect anyone to have all the answers, as long as you’re willing to learn and grow with us.

Syndio is an Equal Opportunity Employer. We are building an inclusive and collaborative workplace as we grow, and we welcome team members regardless of gender/identity, sexual orientation, race or cultural background, religion, physical disability and age.

Join phData, a remote-first data and AI consultancy company with employees across the United States, Latin America, and India. We partner with industry leaders, including Snowflake, AWS, Anthropic, Glean, and dbt, to solve the complex data and AI challenges that slow large enterprises.

We’re growing fast, and we give our people real ownership over their work. We hire top performers and trust them to deliver results.

Why phData?

• Snowflake Implementation Partner of the Year — 7 consecutive years, and 2026 Snowflake AI Partner of the Year
• AWS Premier Tier Services Partner — the highest tier of recognition in the AWS Partner Network
• 2025 Fivetran Partner of the Year (4th consecutive year)
• 2025 dbt Labs Partner of the Year (3x winner) with Visionary partner status
• 2026 KNIME Customer Excellence Partner of the Year
• Preferred Partner in the Anthropic Claude Partner Network
• #1 Partner in Snowflake Advanced Certifications
• 600+ Expert Cloud Certifications (Sigma, AWS, Azure, Dataiku, and more)
• Recognized as an award-winning workplace in the US, India and LATAM

Role Overview

phData is looking for a Principal Analytics Consultant who specializes in Power BI to lead complex analytics engagements and help customers realize measurable value from their data.

In this role, you will combine deep Power BI expertise with strong consulting judgment, executive presence, and delivery leadership. You will guide clients from strategy and discovery through solution design, development, deployment, governance, and adoption. You will translate ambiguous business needs into scalable analytics products that support better decisions and sustainable ways of working with data.

You will work closely with client executives, business stakeholders, technical teams, account leaders, and consultants across phData. You will also help shape Power BI delivery standards, reusable accelerators, enterprise adoption approaches, and the continued growth of the Analytics practice.

Key Responsibilities

• Lead end-to-end Power BI engagements and workstreams, including planning, discovery, requirements, prototyping, development, testing, deployment, enablement, and adoption.
• Establish the overall technical approach, solution architecture, backlog, delivery sequence, and quality standards for scalable Power BI solutions.
• Design and develop Power BI semantic models, reports, dashboards, data products, and self-service analytics experiences that are intuitive, performant, governed, and aligned to business outcomes.
• Apply strong practices in dimensional modeling, DAX, Power Query, SQL, data visualization, metric definition, and performance optimization.
• Connect Power BI solutions to enterprise data warehouses, data marts, lakehouses, semantic models, and other analytical data structures.
• Lead client discovery and working sessions that clarify ambiguous needs, define analytical requirements, align stakeholders, surface tradeoffs, and drive decisions.
• Advise clients on Power BI governance and operating models, including workspace strategy, security, access management, deployment practices, platform administration, adoption, and performance.
• Review and improve existing reports, semantic models, platform configurations, and deployment practices to identify opportunities for optimization, standardization, and scale.
• Manage client expectations through clear communication, status reporting, feedback loops, risk management, transparent escalation, and alignment on decisions and dependencies.
• Provide technical leadership and mentorship to consultants and delivery teams; establish a high bar for quality, usability, maintainability, and client value.
• Contribute to staffing plans, utilization planning, delivery planning, workstream budgets, estimates, and overall project performance.
• Partner with account and practice leaders on discovery, proposals, solution shaping, estimates, and expansion opportunities that deepen client value and support Analytics practice growth.
• Develop reusable Power BI accelerators, frameworks, templates, enablement materials, and points of view that improve delivery consistency and market impact.
• Support backlog development and ongoing enhancement of analytics solutions after initial implementation.

About You

You are a client-focused analytics leader who enjoys solving complex data problems and creating practical, well-designed solutions. You bring strong technical judgment and can move comfortably between business strategy, analytics architecture, hands-on Power BI development, executive conversations, and team leadership.

You are comfortable leading through ambiguity, influencing without authority, and operating in distributed, global teams. You communicate clearly with both technical and business audiences and are energized by helping organizations establish sustainable, value-oriented ways of working with data.

Required Qualifications

Experience

• 7+ years of relevant experience delivering data analytics, business intelligence, or data visualization solutions in an enterprise environment.
• 3+ years of external consulting experience, including ownership of client-facing analytics projects or workstreams from kickoff through completion.
• Experience leading complex delivery teams or workstreams and mentoring consultants or technical practitioners.
• Experience contributing to delivery planning, estimates, staffing, utilization, budgets, proposals, or practice development.

Technical and Functional Skills

• Demonstrated expertise designing and delivering enterprise Power BI solutions, including semantic modeling, report and dashboard development, DAX, Power Query, data visualization, and performance optimization.
• Strong SQL skills and experience working with cloud data warehouses, data marts, lakehouses, semantic models, and analytical data structures.
• Experience with Power BI Service administration and enterprise enablement, including workspace strategy, security roles, access management, deployment practices, platform configuration, governance, and adoption.
• Strong understanding of analytics architecture, data modeling, metric definition, visualization design, usability, scalability, and maintainability.
• Demonstrated ability to translate ambiguous business needs into clear analytical requirements and communicate recommendations, tradeoffs, risks, and dependencies to technical and executive stakeholders.
• Exceptional customer-facing communication, facilitation, project leadership, and stakeholder-management skills.
• Strong problem-solving skills with a passion for learning and applying new technologies, techniques, and procedures.

Preferred Qualifications

Preferred qualifications help candidates stand out but are not required for success in this role.

• Experience scaling Power BI across an enterprise, including governance, operating models, adoption, performance, platform optimization, and change enablement.
• Microsoft Power BI certification, such as Microsoft Certified: Power BI Data Analyst Associate.
• Experience with Power Automate, Power Apps, Copilot Studio, Snowflake, Tableau, Sigma, Alteryx, KNIME, Matillion, Dataiku, Coalesce, or similar modern data and analytics technologies.
• Experience developing reusable accelerators, frameworks, templates, enablement materials, or internal points of view.
• Experience contributing to solution estimates, proposals, discovery activities, and the growth of a consulting practice.
• Experience leading cross-functional teams and influencing senior client stakeholders through complex transformation or modernization initiatives.

Why phData?

• Impactful Work: Partner with leading organizations on meaningful data and AI initiatives.
• Collaborative Culture: Work with a supportive, high-performing global team that values transparency, autonomy, and continuous improvement.
• Growth Opportunities: Access to challenging projects, mentorship, and structured development pathways.
• Values-Driven: We prioritize doing the right thing for our clients, our teams, and our community.

Benefits at phData

US

• Remote-first work environment
• 401(k) plan with company match
• Dental and vision insurance
• Home office equipment stipend
• Annual learning and development stipend
• Competitive compensation, excellent benefits, four weeks of paid time off, 10 holidays, and other perks

phData celebrates diversity and is committed to creating an inclusive environment for all employees. Our approach helps us to build a winning team that represents a variety of backgrounds, perspectives, and abilities. So, regardless of how your diversity expresses itself, you can find a home here at phData. We are proud to be an equal opportunity employer. We prohibit discrimination and harassment of any kind based on race, color, religion, national origin, sex (including pregnancy), sexual orientation, gender identity, gender expression, age, veteran status, genetic information, disability, or other applicable legally protected characteristics. If you would like to request an accommodation due to a disability, please contact us at People Operations.

Join phData, a remote-first data and AI consultancy company with employees across the United States, Latin America, and India. We partner with industry leaders, including Snowflake, AWS, Anthropic, Glean, and dbt, to solve the complex data and AI challenges that slow large enterprises.

We’re growing fast, and we give our people real ownership over their work. We hire top performers and trust them to deliver results.

Why phData?

• Snowflake Implementation Partner of the Year — 7 consecutive years, and 2026 Snowflake AI Partner of the Year
• AWS Premier Tier Services Partner — the highest tier of recognition in the AWS Partner Network
• 2025 Fivetran Partner of the Year (4th consecutive year)
• 2025 dbt Labs Partner of the Year (3x winner) with Visionary partner status
• 2026 KNIME Customer Excellence Partner of the Year
• Preferred Partner in the Anthropic Claude Partner Network
• #1 Partner in Snowflake Advanced Certifications
• 600+ Expert Cloud Certifications (Sigma, AWS, Azure, Dataiku, and more)
• Recognized as an award-winning workplace in the US, India and LATAM

Role Overview

phData is looking for a Principal Analytics Consultant who specializes in Power BI to lead complex analytics engagements and help customers realize measurable value from their data.

In this role, you will combine deep Power BI expertise with strong consulting judgment, executive presence, and delivery leadership. You will guide clients from strategy and discovery through solution design, development, deployment, governance, and adoption. You will translate ambiguous business needs into scalable analytics products that support better decisions and sustainable ways of working with data.

You will work closely with client executives, business stakeholders, technical teams, account leaders, and consultants across phData. You will also help shape Power BI delivery standards, reusable accelerators, enterprise adoption approaches, and the continued growth of the Analytics practice.

Key Responsibilities

• Lead end-to-end Power BI engagements and workstreams, including planning, discovery, requirements, prototyping, development, testing, deployment, enablement, and adoption.
• Establish the overall technical approach, solution architecture, backlog, delivery sequence, and quality standards for scalable Power BI solutions.
• Design and develop Power BI semantic models, reports, dashboards, data products, and self-service analytics experiences that are intuitive, performant, governed, and aligned to business outcomes.
• Apply strong practices in dimensional modeling, DAX, Power Query, SQL, data visualization, metric definition, and performance optimization.
• Connect Power BI solutions to enterprise data warehouses, data marts, lakehouses, semantic models, and other analytical data structures.
• Lead client discovery and working sessions that clarify ambiguous needs, define analytical requirements, align stakeholders, surface tradeoffs, and drive decisions.
• Advise clients on Power BI governance and operating models, including workspace strategy, security, access management, deployment practices, platform administration, adoption, and performance.
• Review and improve existing reports, semantic models, platform configurations, and deployment practices to identify opportunities for optimization, standardization, and scale.
• Manage client expectations through clear communication, status reporting, feedback loops, risk management, transparent escalation, and alignment on decisions and dependencies.
• Provide technical leadership and mentorship to consultants and delivery teams; establish a high bar for quality, usability, maintainability, and client value.
• Contribute to staffing plans, utilization planning, delivery planning, workstream budgets, estimates, and overall project performance.
• Partner with account and practice leaders on discovery, proposals, solution shaping, estimates, and expansion opportunities that deepen client value and support Analytics practice growth.
• Develop reusable Power BI accelerators, frameworks, templates, enablement materials, and points of view that improve delivery consistency and market impact.
• Support backlog development and ongoing enhancement of analytics solutions after initial implementation.

About You

You are a client-focused analytics leader who enjoys solving complex data problems and creating practical, well-designed solutions. You bring strong technical judgment and can move comfortably between business strategy, analytics architecture, hands-on Power BI development, executive conversations, and team leadership.

You are comfortable leading through ambiguity, influencing without authority, and operating in distributed, global teams. You communicate clearly with both technical and business audiences and are energized by helping organizations establish sustainable, value-oriented ways of working with data.

Required Qualifications

Experience

• 7+ years of relevant experience delivering data analytics, business intelligence, or data visualization solutions in an enterprise environment.
• 3+ years of external consulting experience, including ownership of client-facing analytics projects or workstreams from kickoff through completion.
• Experience leading complex delivery teams or workstreams and mentoring consultants or technical practitioners.
• Experience contributing to delivery planning, estimates, staffing, utilization, budgets, proposals, or practice development.

Technical and Functional Skills

• Demonstrated expertise designing and delivering enterprise Power BI solutions, including semantic modeling, report and dashboard development, DAX, Power Query, data visualization, and performance optimization.
• Strong SQL skills and experience working with cloud data warehouses, data marts, lakehouses, semantic models, and analytical data structures.
• Experience with Power BI Service administration and enterprise enablement, including workspace strategy, security roles, access management, deployment practices, platform configuration, governance, and adoption.
• Strong understanding of analytics architecture, data modeling, metric definition, visualization design, usability, scalability, and maintainability.
• Demonstrated ability to translate ambiguous business needs into clear analytical requirements and communicate recommendations, tradeoffs, risks, and dependencies to technical and executive stakeholders.
• Exceptional customer-facing communication, facilitation, project leadership, and stakeholder-management skills.
• Strong problem-solving skills with a passion for learning and applying new technologies, techniques, and procedures.

Preferred Qualifications

Preferred qualifications help candidates stand out but are not required for success in this role.

• Experience scaling Power BI across an enterprise, including governance, operating models, adoption, performance, platform optimization, and change enablement.
• Microsoft Power BI certification, such as Microsoft Certified: Power BI Data Analyst Associate.
• Experience with Power Automate, Power Apps, Copilot Studio, Snowflake, Tableau, Sigma, Alteryx, KNIME, Matillion, Dataiku, Coalesce, or similar modern data and analytics technologies.
• Experience developing reusable accelerators, frameworks, templates, enablement materials, or internal points of view.
• Experience contributing to solution estimates, proposals, discovery activities, and the growth of a consulting practice.
• Experience leading cross-functional teams and influencing senior client stakeholders through complex transformation or modernization initiatives.

Why phData?

• Impactful Work: Partner with leading organizations on meaningful data and AI initiatives.
• Collaborative Culture: Work with a supportive, high-performing global team that values transparency, autonomy, and continuous improvement.
• Growth Opportunities: Access to challenging projects, mentorship, and structured development pathways.
• Values-Driven: We prioritize doing the right thing for our clients, our teams, and our community.

Benefits at phData

US

• Remote-first work environment
• 401(k) plan with company match
• Dental and vision insurance
• Home office equipment stipend
• Annual learning and development stipend
• Competitive compensation, excellent benefits, four weeks of paid time off, 10 holidays, and other perks

phData celebrates diversity and is committed to creating an inclusive environment for all employees. Our approach helps us to build a winning team that represents a variety of backgrounds, perspectives, and abilities. So, regardless of how your diversity expresses itself, you can find a home here at phData. We are proud to be an equal opportunity employer. We prohibit discrimination and harassment of any kind based on race, color, religion, national origin, sex (including pregnancy), sexual orientation, gender identity, gender expression, age, veteran status, genetic information, disability, or other applicable legally protected characteristics. If you would like to request an accommodation due to a disability, please contact us at People Operations.

Description

The Director of Data Governance sits within Quality, Regulatory, and Compliance and leads the evolution of DeepHealth’s data ecosystem into a unified, high-quality enterprise asset. The role owns strategic design, implementation, and continuous improvement of the Data Governance Framework so data is accurate, secure, and ready for advanced analytics and AI initiatives.

Essential Duties and Responsibilities

·       Define and execute a Data Governance roadmap aligned with the Enterprise Information and Governance vision.

·       Review, maintain, and enforce the Data Management Policy and Data Governance Charter against current regulatory and business needs.

·       Facilitate decision-making on data standards and help resolve cross-functional data conflicts.

·       Implement Data Quality Management procedures and establish KPIs for data accuracy, completeness, and consistency.

·       Define enterprise-wide data standards, including metadata management, data lineage, and master data management protocols.

·       Partner with IT and Security so data pipelines support AI applications while maintaining security boundaries.

·       Work with Security to define data classification levels and manage high-risk data access policies.

·       Ensure data practices adhere to applicable global privacy regulations and internal Enterprise Information and Governance mandates.

·       Align data governance priorities with organizational objectives and regulatory requirements.

·       Mentor and develop team members as the data governance capability grows.

Requirements

Minimum Qualifications, Education and Experience

·       Bachelor’s degree in Computer Science, Information Security, Information Management, or a related field, or equivalent practical experience (required).

7 to 10 years of progressive experience in Data Management, Data Governance, or Information Architecture in healthcare, medical technology, or another highly regulated industry (required).

Strong experience with DAMA-DMBOK frameworks and data quality lifecycle management (required).

Deep understanding of data profiling tools, metadata management, and modern data stack concepts (required).

Experience with AI systems in production or product development contexts (required).

Excellent written and oral communication skills, including explaining complex concepts to diverse audiences (required).

High level of integrity and confidentiality (required).

Preferred: Master’s degree or advanced relevant certifications.

Quality Standards

·       Communicates, cooperates, and consistently functions professionally and harmoniously with all levels of supervision, co-workers, visitors, and vendors.

·       Demonstrates initiative, personal awareness, professionalism and integrity, and exercises confidentiality in all areas of performance.

·       Follows all local, regional and country laws concerning employment.

·       Follows all DeepHealth policies and procedures.

·       Follows data privacy, compliance, safety and confidentiality standards at all times.

·       Practices universal safety precautions.

·       Promotes good public relations on the phone and in person.

·       Adapts and is willing to learn new tasks, methods, and systems.

·       Reports to work regularly as scheduled; consistently punctual with respect to working hours, meal and rest breaks, and maintains satisfactory personal attendance in accordance with DeepHealth guidelines.

·       Completes job responsibilities in a quality and timely manner.

Travel

This position requires travel up to approximately 10%.

Working Environment

European Union. Remote-friendly or office-based role.

Physical Demands

The employee must be able to perform the essential duties and responsibilities of the position, with or without reasonable accommodation.

Salary:

115,000.00-130,00.00 EURO

100,000.00-110,000.00 in France

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