Senior Analytics Engineer, People Data

Senior Analytics Engineer, People Data based in Costa Mesa, CA (onsite) for Anduril Industries, with a salary range of USD 166,000 - 220,000 per year.

Responsibilities

• Design, develop, and optimize end-to-end ETL and ELT pipelines to ingest, harmonize, and transform people data from HRIS, ATS, LMS, and other HR systems into the data platform.
• Create and govern scalable, secure data models, schemas, and ontologies for people analytics, ensuring data quality and accessible downstream consumption.
• Contribute to the strategic evolution of the people data platform and tooling, promoting engineering best practices, automation, and a scalable analytics ecosystem using SQLMesh, Iceberg, and Flyte.
• Collaborate with People Analysts, HR Business Partners, and stakeholders to translate analytical needs into robust, well-documented datasets.
• Implement and monitor data quality checks, troubleshoot data issues, and maintain data reliability across systems.
• Monitor the performance of pipelines and models, identify bottlenecks, and implement improvements to support scalability and efficiency.
• Document data pipelines, models, and processes; advocate for data engineering practices such as version control, testing, and CI/CD within the team.
• Enforce data security measures and ensure compliance with internal policies and external regulations (GDPR, CCPA) for employee data privacy.
• Collaborate with enterprise analytics and data engineering teams to align data architecture standards and integrate people data with other business domains.

Requirements

• Minimum of 5 years of experience in Data Engineering, Analytics Engineering, or a similar role focused on building and optimizing data pipelines and infrastructure.
• Advanced SQL expertise for complex data manipulation and proficient Python for scripting and automation.
• Hands-on experience with cloud-based data warehouses (Snowflake, Google BigQuery, AWS Redshift, Databricks/Delta Lake) and data lake storage (S3, Azure Data Lake Storage).
• Strong background in designing and maintaining analytical data models, including dimensional modeling (Kimball).
• Hands-on experience constructing and optimizing ETL/ELT pipelines with dbt, Apache Airflow, Flyte, Dagster, or similar orchestration tools.
• Excellent written and verbal communication, with ability to translate technical concepts for non-technical partners and collaborate across teams.
• Bachelor's degree in Computer Science, Engineering, Data Science, Information Systems, or a related field.
• S solid foundation in data engineering with SQL, Python, and cloud platform experience (AWS, GCP, Azure).

Technologies

• SQL
• Python
• Snowflake
• Google BigQuery
• AWS Redshift
• Databricks/Delta Lake
• AWS S3
• Azure Data Lake Storage
• dbt
• Apache Airflow
• Flyte
• Dagster
• Iceberg
• SQLMesh
• Palantir Foundry
• Terraform
• CloudFormation
• Docker
• Kubernetes
• Tableau
• Power BI
• Looker
• Rippling
• Workday
• Oracle HCM Cloud
• Apache Spark
• Flink

Benefits

• Equity grants included in the majority of full-time offers and are considered part of Anduril's total compensation package.
• Comprehensive benefits package for full-time employees, including health and recovery support.

Preferred Qualifications

• Experience with big data processing frameworks such as Apache Spark and Flink, and with schema evolution or time travel features like Iceberg or Delta Lake.
• Hands-on experience with Palantir Foundry, SQLMesh, Flyte, or similar modern data orchestration platforms.
• Cloud provider certifications (for example, AWS Certified Data Analytics - Specialty or Google Cloud Professional Data Engineer).
• Experience with infrastructure as code and containerization tools such as Terraform, CloudFormation, Docker, or Kubernetes.
• Familiarity with integrating data pipelines with BI tools (Tableau, Power BI, Looker) to optimize dashboards and data accessibility.
• Experience working with enterprise HRIS data sources (Rippling, Workday, Oracle HCM Cloud) and understanding their data models and APIs.
• Strong understanding of HR data concepts, metrics, and HR systems (HRIS, ATS, LMS) with a focus on People Analytics.