Senior Analytics Engineer, People Data

Anduril Anduril · Defense · Costa Mesa, CA · Business Operations : Business Operations : Analytics

Anduril Industries is a defense technology company seeking a Senior Analytics Engineer for their People Data team. The role involves building and maintaining the data infrastructure for HR data, including designing and optimizing ETL/ELT pipelines, developing data models, and ensuring data quality and security. The position requires expertise in SQL, Python, cloud data warehousing, and data modeling, with a focus on transforming raw HR data into analytics-ready datasets to support strategic insights and data-driven decision-making.

What you'd actually do

  1. 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.
  2. 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.
  3. 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).
  4. 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.
  5. Implement and monitor data quality checks, identify discrepancies, troubleshoot data issues, and ensure the reliability and integrity of people data across all systems.

Skills

Required

  • SQL
  • Python
  • ETL/ELT
  • Data Modeling
  • Data Warehousing
  • Data Lakes
  • Data Pipelines
  • Data Quality
  • Data Security
  • GDPR
  • CCPA
  • Cloud Platforms (AWS, GCP, Azure)

Nice to have

  • Apache Spark
  • Apache Flink
  • Apache Iceberg
  • Delta Lake
  • Palantir Foundry
  • SQLMesh
  • Flyte

What the JD emphasized

  • 5+ 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 and optimizing complex ETL/ELT processes and data pipelines using modern tools such as dbt, Apache Airflow, Flyte, Dagster, or similar orchestration platforms.
  • 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.