Senior Data Engineer based in Fairfax County, Virginia, United States, on-site. This role designs, builds, and maintains scalable data pipelines and core data infrastructure to ingest, process, store, and transform structured and unstructured data in a highly regulated client environment. You will develop and operate automated, end-to-end pipelines; optimize data models and schemas; and ensure the reliability, scalability, and security of the enterprise data platform. You will implement robust data quality, validation, and lineage mechanisms and collaborate with data scientists, analysts, and application teams to align data architecture with business and mission needs while advancing data engineering practices. Key responsibilities include: designing and implementing distributed data pipelines using Apache Spark, Kafka, or Flink to support high-volume, near-real-time and batch processing; developing and optimizing data models and storage patterns across relational and non-relational platforms (e.g., PostgreSQL, Snowflake, S3, data lakes) to enable analytics and integration; implementing and operating ETL/ELT workflows using orchestration tools such as Apache Airflow or cloud-native services; establishing data quality validation rules, monitoring, and anomaly detection processes to protect data integrity across production pipelines; building and maintaining data lineage, cataloging, and metadata management for governance, auditability, and regulatory compliance in a highly regulated environment; applying security best practices, including encryption, role-based access contro

Senior Data Engineer based in Fairfax County, Virginia, United States, on-site. This role designs, builds, and maintains scalable data pipelines and core data infrastructure to ingest, process, store, and transform structured and unstructured data in a highly regulated client environment. You will develop and operate automated, end-to-end pipelines; optimize data models and schemas; and ensure the reliability, scalability, and security of the enterprise data platform. You will implement robust data quality, validation, and lineage mechanisms and collaborate with data scientists, analysts, and application teams to align data architecture with business and mission needs while advancing data engineering practices. Key responsibilities include: designing and implementing distributed data pipelines using Apache Spark, Kafka, or Flink to support high-volume, near-real-time and batch processing; developing and optimizing data models and storage patterns across relational and non-relational platforms (e.g., PostgreSQL, Snowflake, S3, data lakes) to enable analytics and integration; implementing and operating ETL/ELT workflows using orchestration tools such as Apache Airflow or cloud-native services; establishing data quality validation rules, monitoring, and anomaly detection processes to protect data integrity across production pipelines; building and maintaining data lineage, cataloging, and metadata management for governance, auditability, and regulatory compliance in a highly regulated environment; applying security best practices, including encryption, role-based access contro