People 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 People Analytics team is at the forefront of transforming how we understand and optimize our workforce. We are a dynamic group of analytical thinkers and storytellers who leverage advanced analytics and robust methodologies to create strategic insights from complex HR data. Collaborating closely with HR Business Partners, Program Management Teams, Business Operations, Talent Acquisition and various cross functional stakeholders we provide actionable insights that drive informed decisions across the entire employee lifecycle; from optimizing talent acquisition and development to enhancing engagement and retention. Our work directly shapes a thriving employee experience, fuels organizational growth, and ensures our people strategy is truly data-driven.

ABOUT THE JOB

This role is central to our People Data & Analytics team, where you will be instrumental in building and maintaining the robust data infrastructure that powers our strategic insights. You'll own the full data lifecycle, from ensuring accurate ingestion and integration of diverse HR data sources, to designing, developing, and optimizing data models and pipelines. Your primary objective will be to transform raw, disparate information into clean, reliable, and analytics-ready datasets, empowering our People Analysts and business stakeholders to unlock deeper understanding of our workforce, enhance employee experience, and drive data-driven decision-making. Success in this role requires a strong technical foundation, meticulous attention to data quality, and a passion for crafting efficient data solutions.

WHAT YOU'LL DO

• Design, build, and optimize robust ETL/ELT pipelines to reliably ingest, integrate, and transform diverse people data from various HR systems (HRIS, ATS, LMS, etc.) into our data platform.

• Develop, maintain, and govern scalable and secure data models, schemas, and ontologies specifically for people analytics, ensuring data quality, consistency, and accessibility for downstream consumption.

• Contribute to the strategic design, development, and evolution of our people data platform and tooling, advocating for engineering best practices, automation, and a scalable analytics ecosystem (e.g., leveraging SQLMesh, Iceberg, Flyte).

• Partner closely with People Analysts, HR Business Partners, and other stakeholders to understand their analytical needs and translate them into robust data solutions, providing well-structured, documented, and reliable datasets.

• Implement and monitor data quality checks, identify discrepancies, troubleshoot data issues, and ensure the reliability and integrity of people data across all systems.

• Continuously monitor the performance of data pipelines and models, identifying bottlenecks and implementing solutions to ensure the efficiency and scalability of our people data infrastructure.

• Create and maintain comprehensive documentation for data pipelines, models, and processes, and champion data engineering best practices (e.g., version control, testing, CI/CD) within the team.

• Implement and enforce strict data security measures and ensure all data handling practices comply with internal policies and external regulations (e.g., GDPR, CCPA) related to employee data privacy.

• Collaborate with broader enterprise analytics and data engineering teams to align on data architecture standards, integrate people data with other business domains, and contribute to the overall evolution of the company's data platform.

REQUIRED QUALIFICATIONS

• 5-7 years of progressive experience in Data Engineering, Analytics Engineering, or a similar role focused on building and optimizing data pipelines and data infrastructure.

• Expert-level proficiency in SQL for complex data manipulation and querying, and advanced Python for scripting, data processing, and automation.

• Extensive experience with cloud-based data warehousing solutions (e.g., Snowflake, Google BigQuery, AWS Redshift, Databricks/Delta Lake) and data lake technologies (e.g., AWS S3, Azure Data Lake Storage).

• Deep understanding and proven experience in designing, implementing, and maintaining robust data models (e.g., dimensional modeling, Kimball methodology) for analytical purposes.

• Hands-on experience building