below marketmost similar roles pay hereabove market
This role pays more than
69%
of similar roles. Most pay
$126,750–$201,625
— the blue band above.
At the midpoint, this role pays about
$184k
versus about
$164k
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
901 open roles
on FindRole.
Listed pay typically runs
$166,000–$220,000
across 858 roles with salary data.
The Senior Data Analyst, Quality joins the Quality Intelligence team to support manufacturing quality operations. As the site analytics lead for the Atlanta facility, you will own and improve production dashboards and pipelines while building new analytics products for evolving programs. You will operate at the intersection of hardware manufacturing and data analytics, pulling from ERP, MES, QMS, and inventory systems to create actionable quality metrics. Key responsibilities include performing root-cause analysis, designing data ontologies, and driving tool adoption among operators. You will utilize Palantir Foundry, Databricks, SQL, and Python to build robust pipelines and AI-assisted tools. This role solves critical manufacturing quality problems by transforming complex production data into real-time insights, ensuring hardware quality gates are met through rigorous data validation and automated monitoring.
What does a Data Analyst earn?
Median $126775 from 72 postings across 23 companies.
Build and maintain production data pipelines and ontologies using Palantir Foundry and Databricks.
Design and operate production dashboards and quality metrics to monitor manufacturing workflows.
Conduct root-cause analysis on data inaccuracies using SQL and Python to ensure data integrity.
Gather requirements from shop floor operators to prioritize and manage the site's analytics backlog.
Develop AI-assisted tools and workflows to automate repetitive manual triage and analysis tasks.
Lead data projects end-to-end from initial requirements gathering through to final deployment and rollout.
Train operators and track dashboard usage to ensure high adoption of analytics tools.
Implement automated data-quality checks and validation rules directly into manufacturing pipelines.
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 in a Data Engineer, Analytics Engineer, or similar role.
At least 1 year of applied data experience in a hardware product engineering environment.
Experience with Foundry, Databricks, or an equivalent cloud lake house.
Strong SQL skills for large, multi-source datasets including joins, window functions, and performance tuning.
Strong applied experience using AI tools with the ability to critically review AI-generated artifacts.
Demonstrated ability to perform root-cause analysis on complex data issues.
Must be eligible to obtain and maintain a U.S. Government security clearance and be subject to ITAR.
Travel up to 25% to Anduril sites and vendors.
Experience supporting analytics for hardware manufacturing across ERP, MES, QMS, PLM, or inventory systems (preferred).
Strong Python for data transformation and scripting (Pandas, PySpark, or equivalent) (preferred).
Experience as an embedded or site-resident engineer at a manufacturing site or greenfield facility (preferred).
Familiarity with quality methodologies such as RCCA / 8D, FMEA, GD&T, IQC / OQC, or control-plan design (preferred).
Defense or regulated-manufacturing experience including ITAR, AS9100, IPC-610, or MIL-STD-1916 (preferred).
Proficiency in software engineering practices including Git, code review, CI, and testing data code (preferred).
Experience integrating LLMs or ML models into analytics workflows (preferred).
Experience mentoring or leading a small team of engineers or analysts (preferred).
Data Quality
Data Observability
SQL
Python
ETL
ELT
Collibra
Informatica
Monte Carlo
Great Expectations
Soda
Alation
Informatica Axon
Data Governance
Data Architecture
HIPAA
GDPR
CCPA
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Statistics
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