Supplier Quality Data Analytics Engineer

Anduril-1; Costa Mesa (CA); Presencial; USD 120.000 - 160.000; Jornada completa

Descripción de la vacante

Anduril Industries is seeking a Supplier Quality Data Analytics Engineer to serve as the analytics partner within the Supplier Quality Engineering organization. You will build data infra, dashboards, and automated workflows to give real-time visibility into supplier performance and non-conformance trends.

Work with SQEs and managers to define KPIs, implement tracking, and drive measurable improvements in supplier quality.

Formación

• Bachelor's degree in a technical field such as analytics or data science.
• 2+ years of analytics, data engineering, quality, or operations engineering experience.
• Expertise in writing complex SQL across multiple data sources.
• Experience with data visualization tools (Tableau, Looker, Power BI, etc.).
• Proficiency with Microsoft Excel including advanced formulas and VBA.
• Proficient in at least one programming language (Python, R, Typescript).

Responsabilidades

• Build and maintain data infrastructure, dashboards, and automated workflows.
• Create supplier quality dashboards and scorecards for leadership.
• Define KPIs and track performance over time.
• Develop automated alerts for non-conformance trends and supplier risk.
• Automate manual data processes to improve efficiency.
• Collaborate with SQE, supply chain, and engineering teams.
• Explore external data sources for risk management insights.
• Educate engineers on analytics tools and drive adoption.
• Embed AI into workflows to identify patterns and predict risk.

Conocimientos

Bachelor's degree in Analytics, Data

2+ years analytics experience

SQL expertise

Data visualization platforms

Excel advanced

Programming for analysis

Educación

Bachelor's degree

Herramientas

Palantir Foundry

Tableau

Looker

Power BI

Streamlit

Dash

Descripción del empleo

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