This role pays less than
56%
of similar roles. Most pay
$146,500–$198,950
— the shaded band above.
At the midpoint, this role pays about
$167k
versus about
$173k
for comparable roles.
Based on 240 similar postings.
Employer
About Anduril Industries
Anduril Industries is a defense technology company that builds advanced hardware and software systems for national security, including autonomous drones, surveillance systems, and the Lattice AI command platform.
Anduril Industries currently has
1697 open roles
on FindRole.
Listed pay typically runs
$146,000–$194,000
across 1504 roles with salary data.
As the Analytics Lead, Manufacturing Quality, you will serve as the resident analytics engineer for the Atlanta facility within the Quality Intelligence team. You will operate at the intersection of hardware manufacturing and data analytics to support production quality engineers on the factory floor. Your daily responsibilities include building and maintaining pipelines and dashboards that transform ERP, MES, and QMS data into actionable insights. You will perform root-cause analysis using SQL and Python, develop AI-assisted tools in Palantir Foundry and Databricks, and manage the site’s analytics backlog while driving user adoption. The role addresses critical manufacturing quality challenges by creating automated monitoring and scorecards to detect quality drift. You must possess expertise in data engineering for hardware products, proficiency with large multi-source datasets, and experience using AI tools like Cursor or Copilot to accelerate development.
Build and maintain production pipelines and dashboards using Palantir Foundry and Databricks.
Develop analytics tools and workflows that automate manual triage for manufacturing quality engineers.
Investigate data quality issues by performing root-cause analysis using SQL and Python.
Gather requirements from floor operators to build a prioritized backlog of site-specific analytics needs.
Implement automated monitoring and validation rules to ensure production data is trustworthy.
Drive user adoption of analytics tools through training, office hours, and usage tracking.
Use AI tools aggressively to accelerate the development of pipelines, tests, and dashboards.
What we're looking for
Bachelor's degree in Computer Science, Mechanical Engineering, Industrial Engineering, or a related technical field from an accredited engineering program.
4+ years of experience as a Data Engineer, Analytics Engineer, or similar role.
At least 2 years of applied data engineering experience in a manufacturing or hardware product engineering environment.
Proficiency in SQL for large, multi-source datasets and Python for data transformation and scripting using Pandas or PySpark.
Experience with Foundry, Databricks, or an equivalent cloud lake house to build and maintain pipelines and dashboards.
Proven ability to perform root-cause analysis on complex data issues and use AI tools critically in daily workflows.
Ability to obtain and maintain a U.S. Government security clearance for ITAR compliance.
Experience with hardware manufacturing systems (ERP, MES, QMS), quality methodologies, or defense-regulated manufacturing (preferred).
Design for Manufacturing
DFMA
CAD
SMT
PCBA
Lean Manufacturing
Six Sigma
Statistical Process Control
Manufacturing Execution Systems
Scripting
Tool Design
Quality Management