Data Engineer (Infrastructure FinOps)

Join Anduril's Infrastructure Engineering organization as a Data Engineer. In this high-impact role, you will architect and build scalable data pipelines, apply software engineering principles, model data, ensure data quality and reliability, and collaborate with various stakeholders. You will have the autonomy to design robust systems that unlock critical business insights from complex, large-scale data.

• Architect, develop, and maintain robust and efficient ETL/ELT pipelines to process petabyte-scale data from a wide variety of sources.
• Collaborate closely with data scientists, analysts, software engineers, and business stakeholders to ensure data quality and reliability.
• Design and implement well-structured, performant data models and schemas in our data warehouse and data lakehouse environments.

• Hands-on expertise with at least one major cloud data platform such as Google BigQuery, Databricks, or an enterprise data system like Palantir Foundry
• Expert-level SQL and query optimization skills on large-scale datasets
• Solid understanding of data modeling concepts, ETL/ELT design patterns, and data warehousing/lakehouse principles
• Must be eligible to obtain and maintain a US Top Secret security clearance
• 5+ years of experience in a data engineering or a similar software engineering role, ideally building data products in a fast-paced environment
• Experience with a major cloud environment (GCP, AWS, Azure), including its security ecosystem and containerization technologies (Docker, Kubernetes)
• Strong programming proficiency in Python
• Hands-on experience with data orchestration and transformation tools like Spark, PySpark, and dbt
• Experience with Infrastructure as Code (e.g., Terraform, CloudFormation) for managing data resources
• Knowledge of real-time data streaming technologies (e.g., Kafka, Flink, Pub/Sub)
• Experience with or a strong interest in learning how to develop data services and data products using modern software architecture and API design principles
• Experience implementing CI/CD pipelines for data applications (e.g., GitHub Actions, Jenkins)
• Familiarity with data visualization tools, such as Tableau