Data Platform Engineer, Anduril Industries

• 2+ years of experience in a combination of data platform engineering, cloud infrastructure, DevOps, or SRE roles
• Eligible to obtain and maintain an active U.S. Department of Defense (DOD) Secret Clearance or higher, and comfort operating in air-gapped, classified, and/or other highly constrained network environments
• Hands-on experience building and maintaining platforms with key components of the modern data stack, such as data lakehouse technologies (e.g., Apache Iceberg), query engines (e.g., Trino/Presto, AWS Athena), transformation tools (e.g., dbt), and real-time stream & batch processing platforms (e.g., Apache Kafka, Apache Spark)
• Experience with Infrastructure-as-Code (IaC), particularly Terraform, for managing complex cloud environments (e.g., AWS, Azure, GCP)
• Strong proficiency in DevOps and software deployment practices, including containerization and orchestration (e.g., Docker, Kubernetes, Helm), GitOps & CI/CD tooling (e.g., ArgoCD, CircleCI), and observability/monitoring/APM platforms (e.g., Datadog, Grafana)
• Procedural fluency in writing, debugging, profiling, testing, and maintaining performant Python and SQL code
• Experience with data pipeline orchestration tooling (e.g., Flyte, Airflow, Dagster)
• Experience writing code in another language (e.g., Go, Java, Scala, JavaScript/TypeScript)
• Proof of delivery — you've owned a project end-to-end from ambiguity to delivered, scalable outcome
• Strong communicator — demonstrated aptitude for strategic partnerships and communication with both technical and non-technical stakeholders
• Engineering fundamentals — Computer Science, Engineering, Physics, or similar background
• Exceptional problem-solving and critical-thinking skills, with the ability to architect robust technical solutions for ambiguous and dynamic platform requirements
• Energized by business impact and a self-starter mindset: you'd rather build an imperfect solution quickly that is used by many people than a perfect solution that collects dust

Desirable

• We are seeking a Senior Data Platform Engineer to design, build, and operate the foundational data infrastructure that powers the Air Dominance & Strike division. In this role, you will be the architect of a scalable, reliable, and easy-to-use platform that enables analytics engineers, data scientists, software engineers, flight test engineers, and field operators to build high-impact analyses and data-driven applications across the product lifecycle — from design and manufacturing through flight test and field operations
• You will combine deep expertise in data pipelines, cloud infrastructure, DevOps, and modern data systems to create a cohesive ecosystem that serves test data infrastructure, fleet management, production analytics, and more
• Applying Site Reliability Engineering (SRE) principles will be key to ensuring the performance and availability of these critical systems, which operate in both commercial cloud and classified environments. You will collaborate closely with platform users — embedding with engineers to understand their workflows and remove friction — ensuring our data capabilities are a force multiplier for the entire division
• Your ability to deploy and maintain these mission-critical solutions will be essential, with occasional travel required for real-world implementation and support
• Lead the design, development, and maintenance of a scalable, self-service data platform that serves as the foundation for analytics and data applications across the organization
• Architect and manage the underlying cloud infrastructure using Infrastructure-as-Code (Terraform), containerization (Docker, Kubernetes), and CI/CD best practices to support the data platform
• Design and implement solutions for multi-server data access in disconnected and intermittently-connected environments, including conflict resolution and merging on reconnect
• Build robust ETL/ELT pipelines in Python (e.g., Polars) leveraging modern DAG-based orchestrators and parallelization techniques to process data
• Implement agentic data processing workflows with strong guardrails, validation, and human-in-the-loop controls to ensure safe and reliable automation
• Build ML-ready feature sets and deploy validated models into production in environments where data quality and integrity are paramount
• Partner with and empower platform users — including analytics engineers, data scientists, and software engineers — by providing robust tooling, clear documentation, and a seamless developer experience
• Apply SRE principles to ensure the data platform is highly available, performant, and observable — establishing SLOs, automating operational tasks, and leading incident response
• Evolve the platform's architecture by evaluating and integrating new technologies from the modern data stack to meet the ever-changing needs of the business