Data Engineer, People Analytics

About the role

Partner closely with the Chief People Officer and People leadership team to translate strategic questions into clear metrics and data products that inform workforce planning, organization design, performance reviews, compensation discussions, and executive reporting
Define and build ETL/ELT pipelines and infrastructure to ingest and standardize data from HRIS and adjacent systems such as Workday, ATS, payroll, benefits, performance platforms, creating a reliable source of truth for headcount, org structure, hiring, attrition, and talent health
Implement data quality, testing, and observability systems to ensure sensitive employee data is accurate and trustworthy
Design privacy-aware data models, transformations, semantic layers, and quality checks so sensitive employee data is accurate, timely, well-documented, and governed appropriately with role-based access controls for decision-making and makes AI-powered people tools and automations reliable enough to ship to production
Partner with People Analytics to translate ambiguous requirements into scalable datasets, dashboards, and self-serve data products that give People leaders, People Partners, and managers visibility into workforce trends while reducing manual overhead.

Responsibilities

• Partner closely with the Chief People Officer and People leadership team to translate strategic questions into clear metrics and data products that inform workforce planning, organization design, performance reviews, compensation discussions, and executive reporting
• Define and build ETL/ELT pipelines and infrastructure to ingest and standardize data from HRIS and adjacent systems such as Workday, ATS, payroll, benefits, performance platforms, creating a reliable source of truth for headcount, org structure, hiring, attrition, and talent health
• Implement data quality, testing, and observability systems to ensure sensitive employee data is accurate and trustworthy
• Design privacy-aware data models, transformations, semantic layers, and quality checks so sensitive employee data is accurate, timely, well-documented, and governed appropriately with role-based access controls for decision-making and makes AI-powered people tools and automations reliable enough to ship to production
• Partner with People Analytics to translate ambiguous requirements into scalable datasets, dashboards, and self-serve data products that give People leaders, People Partners, and managers visibility into workforce trends while reducing manual overhead

Requirements

6+ years of experience in analytics engineering, data engineering, people analytics, or a closely related role, with a track record of building trusted datasets and systems for business decision-making
Hands-on experience working with HRIS and adjacent People systems data (for example Workday, ATS (Ashby), payroll, benefits, performance, or engagement platforms) and know how to reconcile definitions across messy, evolving source systems
Proficiency in SQL and data modeling, and can build production-grade transformations, define durable metric logic, and write performant queries against large analytical datasets
Proficiency in Python (or similar OOP languages) for building data pipelines, automation, and infrastructure
Experience designing systems with data quality, testing, monitoring, and SLAs in mind
Experience with modern data tooling and cloud warehouses such as Snowflake, dbt, Airflow, Fivetran, or similar technologies, along with strong instincts around testing, monitoring, and data quality
Excellent judgment with sensitive and confidential data, and can implement infrastructure and tooling for data privacy, access controls, governance, and thoughtful interpretation of people metrics
Effectiveness in partnering directly with the CPO, People Partners, Finance, and business leaders to turn ambiguous questions into scoped solutions and clearly communicated insights
Leverage AI and agent-based tools to accelerate development, while defining guardrails for safe, production-grade data workflows

Skills

• 6+ years of experience in analytics engineering, data engineering, people analytics, or a closely related role, with a track record of building trusted datasets and systems for business decision-making
• Hands-on experience working with HRIS and adjacent People systems data (for example Workday, ATS (Ashby), payroll, benefits, performance, or engagement platforms) and know how to reconcile definitions across messy, evolving source systems
• Proficiency in SQL and data modeling, and can build production-grade transformations, define durable metric logic, and write performant queries against large analytical datasets
• Proficiency in Python (or similar OOP languages) for building data pipelines, automation, and infrastructure
• Experience designing systems with data quality, testing, monitoring, and SLAs in mind
• Experience with modern data tooling and cloud warehouses such as Snowflake, dbt, Airflow, Fivetran, or similar technologies, along with strong instincts around testing, monitoring, and data quality
• Excellent judgment with sensitive and confidential data, and can implement infrastructure and tooling for data privacy, access controls, governance, and thoughtful interpretation of people metrics
• Effectiveness in partnering directly with the CPO, People Partners, Finance, and business leaders to turn ambiguous questions into scoped solutions and clearly communicated insights
• Leverage AI and agent-based tools to accelerate development, while defining guardrails for safe, production-grade data workflows

Benefits

Nice to Haves
Have worked at a fast-growing start-up, a SaaS company or are eager to contribute in such an environment (being a current Notion user would be great!)

Pay

The compensation offered for this role will be based on multiple factors such as location, the role's scope and complexity, and the candidate's experience and expertise, and may vary from the range provided below. For roles based in San Francisco, the estimated base salary range for this role is $213,000 to $250,000

Schedule

We work from our offices on Mondays, Tuesdays and Thursdays (our Anchor Days) because we do our best thinking and building together in person.