Quality Analytics Site Lead

About the role

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 real-time, 3D command and control center.

Anduril is building Arsenal-1, its first hyperscale manufacturing facility, just south of Columbus, Ohio in Pickaway County. Arsenal-1 is redefining the scale and speed that autonomous systems and weapons can be produced for the United States and its allies and partners. This role is the site applications lead for Quality Intelligence at Arsenal-1, focusing on analytics, manufacturing AI, and vision inspection. You are the resident analytics engineer at the site, accountable for deploying and operating Quality Intelligence tools. This role operates in a hub-and-spoke model, where HQ builds platform-grade analytics centrally, and site engineers localize and run them. The patterns you establish at Arsenal-1 will serve as the template for future factories.

This role is subject to ITAR. Applicants must be eligible to obtain and maintain a U.S. Government security clearance.

Responsibilities

• Operate at the intersection of hardware manufacturing and data analytics, spending time on the shop floor to analyze quality workflows, build analytics tools, and implement actionable dashboards.
• Pull data 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.
• Design, build, and operate production dashboards, pipelines, and quality metrics inspection-data analytics for Arsenal-1. Collaborate with HQ to port proven work to this greenfield site, setting patterns for future programs.
• Run intake and priorities for the site: gather feedback from operators, manufacturing engineers, and program quality leads, turn it into a prioritized backlog, and file evidence-backed requests to HQ for platform improvements.
• Investigate data quality issues: lead root-cause analysis when dashboards are inaccurate or numbers look wrong, using SQL and Python to trace and fix problems at the source.
• Drive technical improvements: implement robust data-quality checks, validation rules, and automated monitoring in pipelines to ensure data trustworthiness.
• Build AI-assisted analytics tools: develop small apps and workflows in Foundry/Databricks to reduce repetitive analyst work by 10x, based on operator feedback.
• Lead data projects end-to-end: partner with cross-functional teams from requirements through deployment, translating program quality problems into configurable data products.
• Drive adoption: train operators, run office hours, track usage, and treat adoption at Arsenal-1 as a deliverable you own.
• Use AI aggressively in your work: draft pipelines, write tests, generate dashboards, explore unfamiliar data, and accelerate repetitive tasks.

Requirements

• 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 2 years of applied data engineering experience in a manufacturing or hardware product engineering environment.
• Understanding of manufacturing workflows, quality gates, and how manufacturing data impacts quality outcomes. Willingness to work on the production floor.
• Production experience with Foundry, Databricks, or an equivalent cloud lakehouse, including building and maintaining pipelines and dashboards.
• Strong SQL skills for large, multi-source datasets: joins across heterogeneous systems, window functions, and performance tuning.
• Strong applied experience using AI tools (Cursor, Claude Code, Copilot, AIP) with the ability to critically review AI-generated artifacts.
• Strong Python skills for data transformation and scripting (Pandas, PySpark, or equivalent).
• Demonstrated ability to perform root-cause analysis on complex data issues.
• Eligible to obtain and maintain a U.S. Government security clearance (ITAR).
• Clear communication skills: ability to explain concepts plainly to directors and precisely to engineers.
• 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.

Preferred Qualifications

• Experience supporting analytics for hardware manufacturing (NPI, ramp, high-volume) across ERP (Oracle, NetSuite, SAP), MES, QMS, PLM (Teamcenter), or inventory/warehouse systems.
• Experience as an embedded or site-resident engineer at a manufacturing or industrial site, or standing up systems 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.

Pay

US Salary Range: $165,000—$218,000 USD. Highly competitive equity grants are included in the majority of full-time offers.

Benefits

Anduril offers top-tier benefits for full-time employees at little to no cost, including:

• Comprehensive health, recovery, and wellness support.