Data Engineer, People Analytics

Who We Are Notion is the collaborative AI workspace where teams and agents think together. We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About The Role As Notion scales, there is a unique opportunity to build the data foundations for People Analytics that enable better decisions around hiring, performance, compensation, and org design - while maintaining strong privacy guarantees for sensitive employee data. In this role, you will design, build, and operate scalable data systems and pipelines that power People data. Your work will ensure that employee data is reliable, secure, and production-ready, enabling both analytics and AI-driven people workflows across the company. This role can be based in either San Francisco or New York City. We work from our offices on Mondays, Tuesdays and Thursdays (our Anchor Days) because we do our best thinking and building together in person. We’re looking for someone who’s excited to work alongside the team during those days. What You'll Achieve - 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 - Design privacy-first data architecture, including access controls, PII handling, and governance standards - 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. Skills You'll Need to Bring - 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 - Ability to leverage AI and agent-based tools to accelerate development, while defining guardrails for safe, production-grade data workflows Nice to Haves - You 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!) Notion is committed to providing highly competitive cash compensation, equity, and benefits. The compensation offered for this role will be based on multiple factor

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 with HRIS and adjacent People systems data (e.g., Workday, ATS (Ashby), payroll, benefits, performance, or engagement platforms) and ability to reconcile definitions across evolving source systems. Proficiency in SQL and data modeling, ability to 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, with strong testing, monitoring, and data quality instincts. Excellent judgment with sensitive and confidential data, and ability to implement infrastructure and tooling for data privacy, access controls, governance, and thoughtful interpretation of people metrics. Ability to partner with CPO, People Partners, Finance, and business leaders to translate questions into scoped solutions and clearly communicated insights. Capacity to leverage AI and agent-based tools to accelerate development while defining guardrails for safe, production-grade data workflows.

Partner with the Chief People Officer and People leadership to translate strategic questions into clear metrics and data products informing 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 (e.g., Workday, ATS, payroll, benefits, performance, engagement platforms), creating a reliable source of truth for headcount, org structure, hiring, attrition, and talent health. Design privacy-first data architecture, including access controls, PII handling, and governance standards. 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 to ensure data is accurate, timely, documented, and governed with role-based access controls for decision-making and to support AI-powered people tools and automations. Collaborate with People Analytics to translate ambiguous requirements into scalable datasets, dashboards, and self-serve data products providing visibility into workforce trends while reducing manual overhead.