Lead Data Engineer

Type of Requisition: Pipeline Clearance Level Must Currently Possess: None Clearance Level Must Be Able to Obtain: None Public Trust/Other Required: None Job Family: Data Science and Data Engineering Job Qualifications: Skills: Data Analysis, Data Analytics, Data Lake, Data Warehousing (DW) Certifications: None Experience: 7 + years of related experience US Citizenship Required: No Job Description: Lead Data Engineer Seize your opportunity to make a personal impact supporting the Case Management Modernization (CMM) Program. The CMM program is an initiative to support the Administrative Office of the US Courts (AO) in developing a modern cloud-based solution to support all 204+ federal courts across the United States. GDIT is your place to make meaningful contributions to challenging projects and grow a rewarding career. The Lead Data Engineer will work as part of the CMM Data Modernization and Governance team responsible for delivering an integrated data governance, engineering, data platform, reporting, analytics, and Artificial Intelligence (AI)/Machine Learning (ML) capabilities that support operational decision-making and fulfill AO's data and analytics objectives in support of the CMM program. The successful candidate will serve as lead for designing, building, testing, and maintaining scalable data engineering components and platform services that power the CMM Program. This role delivers high-quality, secure, and performant data pipelines, transformations, ETL/ELT delivery, data management solutions, and system integrations aligned with federal standards and CMM objectives for modernization, analytics, and operational excellence. The Lead Data Engineer partners closely with the Data Architecture, Data Governance, and Migration teams to ensure engineering work is consistent, auditable, and aligned with CMM's cloud-based CI/CD standards. The Lead Data Engineer will execute the following responsibilities: Data Platform & Architecture - Develop and implement a scalable, secure, cloud-based data platform supporting operational data, reporting, and analytics delivering cloud-based architecture (data lake, lakehouse, or data warehouse). - Ensure alignment with federal security requirements, judiciary architecture standards, data governance policies, and application modernization initiatives. - Engineer multi-tenant, cloud-based environments supporting hybrid/on‑premises systems, enabling SQL, NoSQL, IaaS, PaaS, distributed SQL, multi-modal, and event-driven/streaming databases. - Design and implement auditable data integration patterns across Judiciary systems and external platforms, including the legacy CM/ECF system during the coexistence period, with pipelines integrated into Government-provided CI/CD processes. - Implement and maintain data quality controls, validation rules, and governance-aligned data structures, coordinating with the Data Quality/Validation Engineer to sustain required accuracy and field-completeness thresholds on an ongoing basis. - Drive continuous database and query performance monitoring and optimization, including automated performance tuning, query optimization, and indexing strategies. - Coordinate with the Cloud Data Architect/Data Modeler to ensure engineering implementation stays aligned with the Data Architecture Blueprint and evolving data models. - Document data platform architecture, integrations, data quality metrics, and service statistics, updating this documentation each Program Increment (PI). - Partner with DevSecOps/CI-CD engineering to ensure data pipelines are built, tested, and deployed through Government-provided CI/CD tooling. - Escalate and help resolve technical risks, defects, and dependencies affecting data engineering delivery across the CMM program. - Support development of the Data and Technology Enabler Roadmap across data engineering, reporting/analytics, and AI/ML use cases. Data Engineering & Integration - Design and develop