Data Engineer, Quality Intelligence

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 ANDURIL

Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing the pace, focus, and product-driven culture of Silicon Valley to the defense sector, Anduril is building software and hardware systems that solve the most urgent national security challenges.

ABOUT THE TEAM

Quality Intelligence is a growing, high-leverage HQ team that builds the data analytics and AI that make Anduril's manufacturing programs measurably better. Our customers are program quality leaders, manufacturing engineers, and operators across sites and programs. The work is concrete: dashboards that catch quality drift before customers do, pipelines that turn ERP/MES/QMS information into decisions, and AI tools that compress hours of manual triage into minutes.

ABOUT THE ROLE

This is a builder role. You will own end-to-end data and analytics work that shows up directly on a factory floor. You'll pull data from real production systems (ERP, MES, QMS, Inventory), shape the data into pipelines and ontologies in Palantir Foundry and Databricks, and partner with engineers, ML practitioners, and program quality leads to ship analytics products people actually 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. You will also be expected to be near the hardware. Manufacturing is a building full of people who need answers from your data, and the best engineers on this team are the ones who walk the line, ask "what is this part," and let that shape the schema.

WHAT YOU'LL DO

Support & Maintain Data Analytics: Support analytics and investigations utilizing existing tools and capabilities. Direct users to utilize analytic dashboards, troubleshoot existing dashboard accuracy, and provide modifications and improvements to increase dashboard effectiveness. Investigate Data Quality: Act as a lead technical investigator for data quality issues. When a dashboard is inaccurate or data seems wrong, you will perform deep-dive analysis using SQL and Python to trace the problem back to its source and identify the root cause. Troubleshoot & Optimize: Support the analytics team by troubleshooting data access issues, improving pipeline performance for faster dashboard loads, and ensuring the overall health and reliability of the quality data ecosystem in Foundry. Drive Technical Improvements: Implement robust data quality checks, validation rules, and automated monitoring directly within data pipelines to proactively prevent future data quality issues and eliminate variance. Enable Self-Service Analytics: Partner closely with cross-functional teams and ML Engineers to understand current and future data needs. Build clean, reliable, and well-structured datasets that allow teams to independently create reliable dashboards, reports, and models. Lead Data Projects: Collaborate with partner teams on analytics initiatives from requirements gathering through deployment. Explore efficient ways to deliver the ask, partnering with Data Scientists and other analysts to deliver high-impact, well-rounded solutions. Build AI-Assisted Tools: Develop small apps and workflows (often in Foundry Workshop / AIP) that reduce repetitive analyst work by 10x, leveraging operations knowledge gained directly from conversations with your stakeholders. Capability Discovery: Partner with program quality leads who don't yet know what Quality Intelligence can do for them. Translate their operational problems into data products that already exist or can be configured quickly.

WHO YOU ARE

AI-First Builder: You use AI as part of your daily workflow—Cursor, Claude Code, Copilot, AIP, or whatever fits the task. You review AI-generated code critically, apply it thoughtfully, and always double-check its output. Hands-on & Curious: You are comfortable on the factory floor. You'd rather spend an hour with a manufacturing engineer reviewing a part than guess at column names from your desk. Impact-Driven: You measure your work by what ships and gets used. You'd rather own a small set of pipelines that operators depend on than a wide backlog that no one is asking for. Technical & Pragmatic: You write SQL and Python regularly and readily understand code generated by AI. You can read another engineer's pipeline, identify weaknesses, and suggest concrete improvements. Clear Communicator: You communicate plainly. You can explain a complex data anomaly to a director without jargon, and to an engineer without losing precision.

REQUIRED QUALIFICATIONS

Bachelor’s degree in Data Engineering, Computer Science, Statistics, Engineering, or a related technical field—or equivalent practical experience. 3+ years in a hands-on data role: Data Engineer, Analytics Engineer, BI Engineer, or similar. Production experience with Foundry, Databricks, Snowflake + dbt, or an equivalent cloud lakehouse—you have built and maintained pipelines that other teams depend on. Strong SQL skills on large, multi-source datasets (joins across heterogeneous systems, window functions, and performance tuning). Strong Python skills for data transformation and scripting (Pandas, PySpark, or equivalent). Demonstrated ability to perform root-cause analysis on complex data issues—when a number looks wrong, you can trace it back through the stack and explain why. Comfort using AI coding tools in your daily workflow, with a clear view of where they help and where they don't. Willingness to work in and around manufacturing operations, including periodic time on the production floor and at remote sites. Strong cross-functional communication skills, with the ability to hold substantive conversations with engineers, non-technical operators, and program leadership. Must be a U.S. Person (U.S. Citizen or Permanent Resident) due to ITAR/export control regulations.

PREFERRED QUALIFICATIONS

Experience supporting analytics for hardware manufacturing (NPI, ramp, high-volume) across any of: ERP (Oracle, NetSuite, SAP), MES, QMS, PLM (Teamcenter, Forge), or inventory/warehouse systems. 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). Experience building dashboards in Foundry Workshop / Quiver / AIP, Tableau, or PowerBI, with a clear understanding of how upstream data models drive performance. Strong software engineering practices: Git, code reviews, CI, and testing data code with the same rigor as application code. Experience integrating LLMs or ML models into analytics workflows (e.g., RAG over operational data, AI-assisted triage, or agentic data exploration). Comfort with standard collaboration tools: Slack, Jira, Confluence.

A DAY IN THE LIFE

9:00 AM: Standup with the QI team in Costa Mesa; a teammate flags a scorecard regression from overnight, and you pick up the investigation. 10:30 AM: Pairing with a manufacturing engineer on the production floor to resolve a part the data is mis-classifying—you leave with new test cases for your pipeline.

1. 00 PM: Refactoring an ontology object that has grown unwieldy, using Claude or Cursor to accelerate the change. Ship behind a feature flag.
2. 30 PM: Reviewing the Piece Part Plan onboarding flow with a program quality lead and scoping how it could apply to their program.
3. 30 PM: Focused work: instrumenting a new data-quality check in a Foundry pipeline to catch a class of bad-supplier rows you noticed last week.

5:00 PM: Writing a quick Confluence summary so the next person on the team does not have to relearn what you just figured out.

LOCATION & TRAVEL

Location: Costa Mesa, CA (On-site) Travel: ~10–20% to manufacturing and remote sites. US Person Status: U.S. Person status is required as this position needs to access export-controlled data. US Salary Range

$144,000—$191,000 USD

The salary range for this role is an estimate based on a wide range of compensation factors, inclusive of base salary only. Actual salary offer may vary based on (but not limited to) work experience, education and/or training, critical skills, and/or business considerations. Highly competitive equity grants are included in the majority of full time offers; and are considered part of Anduril's total compensation package. Additionally, Anduril offers top-tier benefits for full-time employees, including: Benefits At Anduril, we invest in our people. Our comprehensive, competitive benefits package (available at little to no cost to employees) ensures you’re supported in health, recovery, and whatever comes next. For more information, Explore Our Benefits. Protecting Yourself from Recruitment Scams Anduril is committed to maintaining the integrity of our Talent acquisition process and the security of our candidates. We've observed a rise in sophisticated phishing and fraudulent schemes where individuals impersonate Anduril representatives, luring job seekers with false interviews or job offers. These scammers often attempt to extract payment or sensitive personal information. To ensure your safety and help you navigate your job search with confidence, please keep the following critical points in mind: No Financial Requests: Anduril will never solicit payment or demand personal financial details (such as banking information, credit card numbers, or social security numbers) at any stage of our hiring process. Our legitimate recruitment is entirely free for candidates. Please always verify communications: Direct from Anduril: If you receive an email from one of our recruiters, it will only come from an @anduril.com address. Via Agency Partner: If contacted by a recruiting agency for an Anduril role, their email will clearly identify their agency. If you suspect any suspicious activity, please verify the agency's authenticity by reaching out to View email address on click.appcast.io. Exercise Caution with Unsolicited Outreach: If you receive any communication that appears suspicious, contains grammatical errors, or makes unusual requests, do not engage. Always confirm the sender's email domain is @anduril.com before providing any personal information or clicking on links. What to Do If You Suspect Fraud: Should you encounter any questionable or fraudulent outreach claiming to be from Anduril, please report it immediately to View email address on click.appcast.io. Your proactive caution is invaluable in protecting your personal information and upholding the security and trustworthiness of our recruitment efforts. Data Privacy To view Anduril's candidate data privacy policy, please visit By submitting your application, you consent to Anduril Industries using a third-party service provider to conduct pre-employment risk, integrity, and due diligence screening and assessing potential risks as part of your application process. This third-party service provider provides risk-intelligence services that may include analysis of sanctions and watchlists, adverse media, public-record information, and other lawful open-source or commercial data sources. This third-party service provider does not act as a consumer reporting agency. Use of this provider helps to ensure compliance with applicable laws and protect technology, intellectual property, and organizational security.