Senior Data Architect

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 Engineering, Data Lake, Data Warehousing (DW), Enterprise Data

Certifications:

None

Experience:

10 + 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 Sr. Data Architect will be 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 the lead architect, engineer, and operator for all data infrastructure supporting the CMM program. This role is responsible for designing, implementing, operating, and continuously improving cloud-based data platforms and pipelines spanning the full technical data lifecycle—including ingestion, storage, transformation, integration, migration, archival, and ongoing operations. The Data Architect ensures all solutions align with government-provided CI/CD processes and comply with federal security, privacy, and data protection requirements.

The Sr. Data Architect will execute the following responsibilities:

Data Platform & Architecture

• Design and implement a scalable, secure, cloud-based data platform supporting operational data, reporting, and analytics delivering a cloud-based architecture (data lake, lakehouse, or data warehouse)
• Develop and document data flows, structures, standards, and governance alignment.
• Ensure alignment with federal security requirements, judiciary architecture standards, data governance policies, and application modernization initiatives.
• Architect multi-tenant, cloud-based environments supporting hybrid/on‑premises systems, enabling SQL, NoSQL, IaaS, PaaS, distributed SQL, multi-modal, and event-driven/streaming databases.
• Ensure logical/physical data isolation, tenant-level security, and resource allocation controls.
• Maintain monthly platform uptime of 99.9%+.
• Maintain version-controlled architecture diagrams, data models, performance metrics
   

Data Engineering & Integration

• Implement operational databases, document storage, indexing services, schemas, and secure data APIs.
• Implement Infrastructure as Code (IaC) for database provisioning and configuration.
• Continuously monitor and optimize database/query performance via automated tuning and indexing strategies.
   

Data Migration & Archiving

• Develop a Data Migration Strategy including profiling, mapping, testing, anomaly handling, and rollback procedures.
• Develop a Data Archival Strategy covering archive creation, migration, storage tiers, retention schedules, and access controls.
• Implement batch and real-time data exchange with Judiciary systems
• Design, test, and implement DR and high availability strategies
• Deliver migration documentation for scripts, transformations, and validation results.

QUALIFICATIONS:

• MA/MS degree with 12+ years of general experience in information systems and 10+ years of specialized experience.
• Experience may be considered in lieu of degree as follows: HS (16+ years), AA/AS (14+ years), BA/BS (12+ years), Doctorate Degree/Ph.D. (9+ years).
• Deep experience designing data architecture using AWS data services and modern application patterns.
• Define scalable, secure operational data models and patterns that enable application features and service integrations.
• Establish and enforce operational data governance guardrails including integrity controls, cost efficiency, and resilience.
• Establish platform integration patterns for ETL/ELT pipelines, APIs, and downstream consumption layers supporting BI and data product.
• Expertise in relational an