People Data Analyst

The Role:

We are looking for a highly analytical and mission-driven People Data Analyst to join our People team. In this role, you’ll be the connective tissue between People Systems, Data Engineering, and People leadership, translating raw People and business data into the insights that shape how we hire, organize, and grow.

You’ll partner closely with our People Systems Engineer and Data Engineering team to help define the data model that underpins our People stack, and you’ll own turning that foundation into dashboards, reports, and analysis that recruiting, People leadership, and the broader business leadership team rely on to make decisions.

This is a build-from-the-ground-up opportunity: you won’t inherit a mature analytics function with years of dashboards and definitions already in place. You’ll help define what “good” looks like, the metrics that matter, the data model that supports them, and the reporting infrastructure that scales with a hypergrowth company. You’ll also help define how AI augments this work, from automating recurring reporting to building natural-language interfaces over People data in partnership with People Systems.

What You’ll Do

• Design and build dashboards and self-serve reporting (e.g. in Tableau, Superset) once the underlying data infrastructure is in place, and own their accuracy and adoption going forward.
• Define and standardize core People metrics time-to-fill, attrition, span of control, headcount vs. plan, and similar in partnership with People leadership.
• Translate business questions from People and Recruiting leadership, and executive stakeholders into clear analytical approaches, and deliver insights that directly inform decisions.
• Partner with the People Systems Engineer and Data Engineering team to define and evolve the People data model.
• Connect People data to broader business metrics (e.g. headcount vs. revenue or production output, productivity, cost per hire relative to business growth) to give business leadership a complete picture of how people investment tracks with company performance.
• Partner with People Systems to identify and prioritize opportunities to use AI and natural language interfaces to make People data more accessible; helping non-technical stakeholders query and explore data without needing to build a new report each time.
• Own data quality and governance for People analytics; establishing definitions, validating accuracy, and ensuring leadership is informed.