Databricks Data Engineer

Responsibilities The Databricks Data Engineer will be responsible for the hands-on build-out of a Government-owned Databricks workspace and the data ingestion/integration work needed to consolidate agency business system data. This includes designing and implementing data pipelines from core enterprise systems, implementing Unity Catalog for data governance, configuring MLflow for machine learning workflows, and developing comprehensive documentation to support sustainment beyond the pilot. This role is 100% Remote. Other Responsibilities Include: Build out and configure a dedicated Government workspace within the existing Databricks environment Design and implement data ingestion pipelines from core agency business systems including financial, HR, CRM, and ITSM systems Leverage native/built-in connectors where source systems support them; design custom integration approaches for legacy systems Normalize and prepare ingested data within Databricks for consumption by downstream visualization/reporting tools Implement Databricks Unity Catalog for centralized data governance, metadata management, active auditing, and end-to-end lineage tracking Review current configuration, assess security controls for CUI/PII/PHI/financial data, and implement improvements Develop comprehensive "as-built" documentation including physical/logical architecture diagrams, automated data dictionaries, and SOPs Document data sources, integration methods, and data lake architecture decisions to support sustainment Qualifications Required Qualifications: 5 years work experience with BS/BA; 3 years with MS/MA US Citizenship Active DoD Secret clearance 2 years working on the Databricks platform Strong proficiency in PySpark, Spark SQL, and Python for large-scale data processing and pipeline development Hands-on experience with Unity Catalog administration, including metastore management, access policies, and data lineage Experience with pipeline orchestration tools (Airflow, Databricks Workflows