Data Analyst, Quality at Anduril Industries · LumiJobs

Responsibilities

Intersection of Analytics and Manufacturing: You will operate at the intersection of hardware manufacturing and data analytics. You are not afraid to spend time on the shop floor analyzing quality workflows, building analytics tools for said workflows and implementing them in well-designed, actionable dashboards.
Production Data: You'll pull from production systems (ERP, MES, QMS, inventory), build pipelines and ontologies in Palantir Foundry and Databricks, and partner with manufacturing engineers, ML practitioners, and program quality leads to ship analytics products operators depend on.
Develop & Operate Analytics for Arsenal 1: You will design, build, and operate the production dashboards, pipelines, and quality metrics inspection-data analytics the site runs on. Arsenal 1 is greenfield, so you will collaborate closely with HQ to port over proven work. Well thought out decisions you make set the pattern for future programs.
Run intake and priorities for the site: hold a standing feedback loop with operators, manufacturing engineers, and program quality. Turn what you hear into a prioritized, visible backlog — what you can configure this week, what needs HQ build time, and what we are deliberately not doing — and file crisp, evidence-backed asks back to HQ so the platform gets better.
Investigate data quality: When a dashboard is inaccurate or a number looks wrong, you are the lead investigator. Deep-dive analysis in SQL and Python, trace problems through the stack, identify the root cause, and fix it at the source.
Drive technical improvements: You will implement robust data-quality checks, validation rules, and automated monitoring directly in the pipelines. Your data is trusted because you made it provably trustworthy.
Build AI-assisted analytics tools: small apps and workflows in Foundry / Databricks that reduce repetitive analyst work by 10x, grounded in what you have learned from operators on the floor.
Lead data projects end-to-end: partner with cross-functional teams from requirements through deployment. Translate program quality leads' problems into data products that already exist or can be configured quickly and own the rollout.
Drive adoption: a dashboard nobody opens is ineffective. You will train operators, run office hours, track usage, and treat adoption at Arsenal 1 as a deliverable you own, not a downstream side effect.
AI Use: You will be expected to use AI aggressively in your own work: to draft pipelines, write tests, generate dashboards, explore unfamiliar data, and accelerate the repetitive parts of the job.
Collaboration: Collaborate with cross-functional teams, which requires regular interaction with production and manufacturing stakeholders and frequently working directly on the production floor.

Qualification

Bachelor's degree in Computer Science4+ years in a Data EngineerYou understand how manufacturing worksExperience with FoundryStrong SQL on largeEligible to obtain and maintain a UYou communicate plainlyFamiliarity with quality methodologiesSoftware engineering practices

Required

Bachelor's degree in Computer Science, Mechanical Engineering, Industrial Engineering, or a related technical field from an accredited engineering program.
4+ years in a Data Engineer, Analytics Engineer, or similar role with at least 1 year applied data experience in hardware product engineering environment.
You understand how manufacturing works: the workflows, the quality gates, and how manufacturing data drives or degrades quality outcomes. You are willing to work in and around manufacturing operations, including time on the production floor.
Experience with Foundry, Databricks or an equivalent cloud lake house. You have built and maintained pipelines and dashboards other teams depend on.
Strong SQL on large, multi-source datasets: joins across heterogeneous systems, window functions, and performance tuning.
Strong applied experience using AI (Cursor, Claude Code, Copilot, AIP) with ability to review AI-generated artifacts critically. You are aware of the mistakes AI tools can make, with a clear view of where they help and where they don't.
Demonstrated root-cause analysis on complex data issues. When a number looks wrong, you can trace it back through the stack and explain why.
Eligible to obtain and maintain a U.S. Government security clearance (this role is subject to ITAR).
You communicate plainly: to a director without jargon, to an engineer without losing precision.
Based in or willing to relocate to the greater Columbus, OH area and work on-site at Arsenal 1 in Ashville, OH.
Travel up to 25% to Anduril sites and vendors.
U.S. citizenship is required pursuant to contractual obligations.

Preferred

Experience supporting analytics for hardware manufacturing (NPI, ramp, high-volume) across any of ERP (Oracle, NetSuite, SAP), MES, QMS, PLM (Teamcenter), or inventory / warehouse systems.
Strong Python for data transformation and scripting (Pandas, PySpark, or equivalent).
Experience as an embedded or site-resident engineer at a manufacturing or industrial site, or standing up systems and data at a greenfield facility.
Familiarity with quality methodologies: RCCA / 8D, FMEA, GD&T, IQC / OQC, control-plan design.
Defense or regulated-manufacturing experience (ITAR, AS9100, IPC-610, MIL-STD-1916, or similar).
Software engineering practices: Git, code review, CI, and testing data code with the same rigor as application code.
Experience integrating LLMs or ML models into analytics workflows: RAG over operational data, AI-assisted triage, or agentic data exploration.
Experience mentoring or leading a small team of engineers or analysts.

Data Analyst, Quality

Responsibilities

Qualification

Required

Preferred

Benefits

Company

Anduril Industries

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