Supplier Quality Data Analytics Engineer

Anduril Industries, Inc.; Costa Mesa (CA); On-site; USD 120,000 - 160,000; Full time

Job summary

Anduril Industries, Inc. is seeking a Supplier Quality Data Analytics Engineer to join the Supplier Quality Engineering team in California.

You will build data infrastructure, dashboards, and automated workflows that provide real-time visibility into supplier performance, non-conformance trends, and incoming inspection results. Using Palantir Foundry as the central platform, you will conduct ad-hoc analysis, develop interactive dashboards, and write back to our systems of record, driving

Qualifications

• Bachelor's degree or equivalent in analytics, CS, industrial, or quality engineering.
• 2+ years in analytics, data engineering, or quality/operations roles in hardware manufacturing.
• Expert SQL skills across multiple data sources.
• Experience with data visualization and Palantir Foundry is a plus.
• Proficiency in Excel with advanced functions and VBA.

Responsibilities

• Transform ERP and QMS data into structured datasets using SQL.
• Build dashboards and automated workflows in Palantir Foundry for supplier quality reporting.
• Create supplier scorecards combining quality, delivery, and responsiveness data.
• Define KPIs like supplier PPM and SCAR closure rate with time-tracking.
• Develop automated alerting for non-conformance trends and risky suppliers.
• Automate manual data compilation and report generation to reduce toil.
• Manage cross-functional projects with clear timelines and stakeholders.
• Incorporate external data sources for supplier risk insights.
• Educate engineers on analytics tools and drive user adoption.
• Embed AI patterns in workflows to identify non-conformance signals.

Skills

SQL

Data analysis

Cross-functional collaboration

Quality engineering mindset

Education

Bachelor's degree in Analytics/CS/Engineering

Relevant technical field

Tools

Tableau

Power BI

Looker

Palantir Foundry

Excel

Python

Job description

Supplier Quality Data Analytics Engineer

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 Supplier Quality Engineering team is responsible for ensuring that externally sourced components and assemblies meet Anduril's rigorous quality standards. The team works closely with suppliers, production, and engineering to drive corrective actions, monitor supplier performance, and continuously improve incoming material quality across Anduril's product portfolio. As the organization scales rapidly, data-driven decision making is critical to identifying trends, prioritizing supplier interventions, and measuring the effectiveness of quality programs.

ABOUT THE JOB

As a Supplier Quality Data Analytics Engineer, you will be embedded within the Supplier Quality Engineering organization and serve as the team's dedicated analytics partner. You will build and maintain the data infrastructure, dashboards, and automated workflows that give supplier quality engineers real-time visibility into supplier performance, non-conformance trends, corrective action effectiveness, and incoming inspection results. Using Palantir's Foundry platform as your central resource, you will conduct ad-hoc analysis, produce interactive dashboards, and develop automated workflows that write back to our systems of record. You will gain a deep understanding of supplier quality processes — from incoming inspection and SCAR management to supplier audits and approved supplier list governance — and craft tools that drive measurable improvements in supplier quality outcomes.

WHAT YOU'LL DO

• Use SQL to transform raw ERP and QMS data extractions into structured datasets within a centralized GitHub repository, with a focus on supplier quality metrics (PPM, DPMO, SCAR cycle time, lot acceptance rates)
• Use Palantir's Foundry platform to generate dashboards and automated workflows code repositories for supplier quality reporting
• Build and maintain supplier scorecards that aggregate quality, delivery, and responsiveness data to support supplier review boards and business decisions
• Work with Supplier Quality Engineers and managers to define key performance metrics (e.g., supplier PPM, SCAR closure rate, first pass yield) and implement systems for tracking over time
• Develop automated alerting and escalation workflows for non-conformance trends, repeat defects, and at-risk suppliers
• Eliminate repetitious processes — such as manual inspection data compilation, SCAR status tracking, and supplier report generation — with programmatic automation
• Manage cross-functional projects with clear and concise communication on timelines, partnering with supply chain analytics, production quality, and engineering teams
• Assess and incorporate external data sources that could bring valuable insight to supplier quality risk management
• Educate supplier quality engineers with training and documentation on analytics tools, and drive user adoption through a continual feedback loop
• Embed AI into workflows via Palantir's Foundry platform to help identify patterns in non-conformance data, predict supplier risk, and drive signal from noise

REQUIRED QUALIFICATIONS

• Bachelor's degree in Analytics, Data Science, Computer Science, Industrial Engineering, Quality Engineering, or related technical field
• 2+ years of experience in analytics, data engineering, quality engineering, or operations engineering roles, preferably in complex hardware technology or manufacturing industries
• Expertise in SQL with demonstrated ability to write complex queries across multiple data sources
• Expertise in data visualization platforms such as Tableau, Looker, Power BI, Streamlit, Dash, or Palantir Foundry
• Strong proficiency in Microsoft Excel including advanced formulas, live database connections, and VBA
• Proficient in at least one additional programming language such as Python, R, Typescript, or similar, for analysis, data visualization, and automation
• Ability