About the role
Hadrian - Manufacturing the Future Hadrian is building autonomous factories that help aerospace and defense companies manufacture rockets, satellites, jets, and ships up to 10x faster and up to 2x cheaper. By combining advanced software, robotics, and full-stack manufacturing, we are reinventing how America produces its most critical parts. We’re accelerating our mission with the launch of Factory 3 in Mesa, Arizona, a 290,000-square-foot facility creating 350 new jobs. We are expanding rapidly to support thousands of future hires, launching Hadrian Maritime to expand into naval production, and introducing a Factory-as-a-Service model that delivers complete systems instead of individual parts. Hadrian is backed by leading investors including T. Rowe Price, Lux Capital, Founders Fund, and Andreessen Horowitz, our fast-growing team is united around reindustrializing American manufacturing for the 21st century and beyond.
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 can trust the numbers without having to double-check them • Conduct ad hoc and deep-dive analyses (e.g. attrition drivers, hiring funnel efficiency, organizational design) that go beyond standard reporting to answer emerging business questions What We’re Looking For 6+ years of experience in data analytics, business intelligence, or people analytics, with a track record of delivering insights that influenced real business or People decisions • Strong SQL skills and comfort working directly in a modern data warehouse (e.g. Snowflake, BigQuery, Redshift) to build and maintain your own queries and data models, rather than relying solely on pre-built tables • Hands-on experience building dashboards and reports in a BI tool such as Looker, Tableau, Superset including the underlying data modeling, not just the visualization layer • Experience partnering with engineering or data engineering teams to define data models and