Data Engineer Journeyman is responsible for designing, building, and operating scalable data pipelines and platforms that ingest, process, and store structured and unstructured data to support mission-critical use across the enterprise data environment. Leveraging modern batch and streaming frameworks, this role develops optimized data models, transformation logic, and storage solutions that enable analytics, reporting, and advanced data use cases for business and technical stakeholders. The role implements data quality, lineage, and governance practices while ensuring security and compliance in a highly regulated federal data context. This position collaborates with cross-functional teams including data scientists, analysts, and security stakeholders to understand data requirements, refine data workflows, and continuously improve platform reliability, performance, and resilience. The engineer troubleshoots pipeline issues, documents data architecture and pipelines, and contributes to ongoing modernization and automation of data engineering processes and tooling across the client environment. Key responsibilities include: design, develop, and maintain batch and streaming data pipelines using frameworks such as Apache Spark, Kafka, or equivalent cloud-native services to support high-volume ingestion and processing for mission-critical workloads; build and optimize data models and schemas (including star, snowflake, and normalized designs) that support analytical, reporting, and operational use cases across the enterprise; implement data validation, profiling, and monitoring

Data Engineer Journeyman is responsible for designing, building, and operating scalable data pipelines and platforms that ingest, process, and store structured and unstructured data to support mission-critical use across the enterprise data environment. Leveraging modern batch and streaming frameworks, this role develops optimized data models, transformation logic, and storage solutions that enable analytics, reporting, and advanced data use cases for business and technical stakeholders. The role implements data quality, lineage, and governance practices while ensuring security and compliance in a highly regulated federal data context. This position collaborates with cross-functional teams including data scientists, analysts, and security stakeholders to understand data requirements, refine data workflows, and continuously improve platform reliability, performance, and resilience. The engineer troubleshoots pipeline issues, documents data architecture and pipelines, and contributes to ongoing modernization and automation of data engineering processes and tooling across the client environment. Key responsibilities include: design, develop, and maintain batch and streaming data pipelines using frameworks such as Apache Spark, Kafka, or equivalent cloud-native services to support high-volume ingestion and processing for mission-critical workloads; build and optimize data models and schemas (including star, snowflake, and normalized designs) that support analytical, reporting, and operational use cases across the enterprise; implement data validation, profiling, and monitoring