Data Engineer, Quality Intelligence

Anduril Industries • Costa Mesa, CA

15h • Onsite

About The Position

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. 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.

Requirements

• 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.

Nice To Haves

• 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.

Responsibilities

• 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.
• 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.
• 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.
• Implement robust data quality checks, validation rules, and automated monitoring directly within data pipelines to proactively prevent future data quality issues and eliminate variance.
• 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.
• 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.
• 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.
• 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.

Benefits

• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level