Performance & Data Optimization Engineer

Type of Requisition:
Regular
Clearance Level Must Currently Possess:
None
Clearance Level Must Be Able to Obtain:
None Public Trust/Other Required:
BI Full 6C (T4)
Job Family:
Cyber and IT Risk Management Job Qualifications:
Skills:
GitHub, Jira and Confluence administration, Web Application Security Certifications:
None Experience:
5 + years of related experience US Citizenship Required:
No
Job Description:

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 Performance & Data Optimization 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 be responsible for monitoring and optimizing the performance of the enterprise cloud data platform, focusing on database performance, query execution, indexing strategies, and overall platform efficiency. This role identifies bottlenecks, tunes queries and platform configurations, and partners with data engineering and platform teams to ensure the CMM Data Modernization & Governance platform runs efficiently, reliably, and cost-effectively at scale.

THE PERFORMANCE & DATA OPTIMIZATION ENGINEER WILL EXECUTE THE FOLLOWING RESPONSIBILITIES

- Optimize databases and platform performance across cloud data warehouses/lakes, including query execution, indexing, partitioning, and caching.

- Monitor system health; manage incidents, events, and operational reporting.

- Diagnose and resolve performance bottlenecks in queries, pipelines, and resource utilization (CPU, memory, storage, network, I/O, concurrency).

- Analyze and tune SQL, ETL/ELT, data models, ingestion patterns, and workload performance for efficiency and cost.

- Establish and maintain SLAs, baselines, dashboards, and automated monitoring/alerting.

- Plan capacity, perform workload analysis, and guide scaling and cost-optimization decisions.

- Collaborate with platform engineers, DBAs, architects, and application teams to optimize compute/storage configurations and resolve issues.

- Maintain access controls, user roles, and identity integrations including SSO, MFA, and JENIE-based least privilege enforcement.

- Provide disaster recovery and continuity options including high availability, fault tolerance, and automated failover.

- Integrate DevSecOps tools and processes with enterprise systems to ensure unified security posture.

- Manage centralized secrets with automated rotation, access logging, and policy enforcement.

- Embed SAST, DAST, SCA, and CSPM tools into CI/CD for continuous assessment and remediation.

- Implement automated, continuous 24/7 monitoring for security, performance, and compliance with real-time dashboards.

- Ensure automated SBOM generation and management for all deployed artifacts.

- Provide diagnostics, metrics gathering, and performance tuning; support canary releases for testing.

- Collaborate with data governance and data quality teams to ensure performance optimization efforts align with data standards and controls.

- Collaborate with Data Platform Engineers, Database Administrators, Data Architects, and Data Engineers to resolve performance issues.

- Perform automated, full-stack health checks at agreed intervals.

- Deliver monthly reports covering incidents, stability, performance, configurations, ticket volume, and resolution times.

- Support high availability, disaster r