Data Engineer (DoD Secret | Remote)

4+ years of experience in Data Engineering or Analytics Engineering Proficient in SQL and Python, with experience building modular, version-controlled transformations Hands-on with Apache Airflow, Apache Spark, dbt, and data lake frameworks (Iceberg, Trino, Athena) Strong understanding of ETL/ELT design, data modeling, and governance in distributed systems Familiar with AWS (Glue, S3, Lambda, Athena, EMR) and cloud-native data architectures Excellent collaborator with experience in cross-functional environments (DevSecOps, Data Science, Security)

Build and maintain end-to-end Ingest → Transform → Expose pipelines using Airflow, Spark, dbt, and Iceberg. Ingest and normalize structured and unstructured data (HL7, FHIR, PDF, JSON) for analytics and AI/ML use cases. Map datasets to FHIR and OMOP standards to enable interoperability and decision support. Implement schema versioning and governance to ensure traceability and audit-ready lineage. Collaborate with DevSecOps and Data Science teams to deliver AI-ready datasets for predictive analytics and readiness forecasting. Optimize data performance across distributed environments while ensuring compliance with DoD Responsible AI and NIST AI Risk Management frameworks.