opengreenhousea16z
Data Analyst, Talent Acquisition
Anduril Industries
LocationBoston, Massachusetts, United States, Costa Mesa, CA (HQ)
Last observed2026-07-02 05:06:11.233087
Job ida16z-anduril-industries:greenhouse:5172166007
Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing the expertise, technology, and business model of the 21st century’s most innovative companies to the defense industry, Anduril is changing how military systems are designed, built and sold. Anduril’s family of systems is powered by Lattice OS, an AI-powered operating system that turns thousands of data streams into a realtime, 3D command and control center. As the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years. ABOUT THE TEAM The Talent Operations Systems team is responsible for the systems, data, process, and infrastructure that make Anduril's recruiting function work at scale. We work in a highly cross-functional manner, sitting between TA leadership, recruiters, business leaders, and the people data team to drive recruiting processes and systems and turn fragmented operational data into a trusted, decision-ready data product. Our work directly shapes how Anduril finds, evaluates, and hires the engineers, operators, and builders behind the future of defense, and it's how recruiting leadership knows where to invest, what's working, and where the funnel is breaking. ABOUT THE JOB We are looking for an Data Analyst, Talent Acquisition to join our rapidly growing Talent Operations team. In this role, you will be the analytics engineer embedded inside our TA function, responsible for transforming recruiting and people data into the models, metrics, tools and applications that recruiting leadership, sourcers, and recruiters use every day to run the function. You will partner directly with the people doing the work, learn the underlying recruiting processes end-to-end, and translate fuzzy business questions into a coherent semantic/metrics layer and self-service tools and applications that users trust and regularly turn to. You will also partner with the People Data team to own the ingestion and warehousing layer where it matters — but most of your time will go to modeling, metrics, dashboards, and stakeholder partnership. This will require strong SQL and data transformation framework know-how, real experience with a semantic/metrics layer and self-service BI tooling (we use Foundry), working Python for custom API connectors, and prior depth in recruiting, talent acquisition, or people analytics data. If you are someone who is genuinely curious about the TA domain, who wants to sit with users and learn their processes before writing a line of SQL, who has a real point of view on what "good" looks like for recruiting metrics, and who enjoys fast but responsible iteration and builds, then this role is for you. WHAT YOU’LL DO Partner directly with recruiting leadership, sourcers, and recruiters — learn the recruiting processes end-to-end and understand the context behind the data and translate fuzzy business questions into specific, well-scoped data products. Own models for sourcing funnels, candidate journey, requisition lifecycle, sourcer/recruiter activity, outreach, and hiring outcomes — so the same numbers show up the same way everywhere they're consumed. Build and maintain a semantic/metrics layer that defines metrics once and exposes them consistently to self-serve dashboards for downstream consumers. Ship self-service dashboards (in Foundry) — for example: funnel health, time-to-fill, sourcer productivity, outreach response rates, source-of-hire, pipeline coverage by req, conversion by stage and segment — and iterate with users until they actually self-serve. Write and maintain custom connectors for systems without off-the-shelf integrations (for TA tools), and partner with People Data Team on orchestration, scheduling, and the warehouse layer that everything sits on. Partner with TA Ops team to enforce data quality so lead
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