Data Governance Lead

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 Governance Lead 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 be responsible for developing, implementing, and operationalizing a comprehensive data governance framework to accelerate CMM modernization efforts. This role ensures alignment with Judiciary policies, practices, and the current Data Governance Roadmap, while driving organizational adoption through robust change management strategies. The Data Governance Lead will guide the design of standards, oversee daily governance operations, and foster a data‑driven culture across the AO and local courts.

The Sr. Data Governance Lead will execute the following responsibilities:

Data Governance Strategy & Standards

• Develop and maintain an enterprise-level data governance framework tailored to CMM program needs and varying court types.
• Update and refine the data governance roadmap using current plans and industry best practices.
  Create comprehensive data standards, SOPs, and policies covering data quality, metadata, privacy, sharing, classification, and retention.
• Leverage existing Judiciary guides, conventions, and tools; recommend enhancements for system integration and automation to support a cohesive Data Strategy.
• Define and document data classification, access control, privacy, usage, and sharing policies.
• Establish roles, workflows, responsibilities, success metrics, and repeatable processes for data quality and compliance.
• Provide recommendations, implementation guidance, and oversight for metadata management, data catalogs, lineage processes, and governance platform tooling in coordination with AO and the Enterprise Data Office.
• Use an industry-standard maturity model to assess governance progress, establish milestones, and report status to stakeholders.
• Implement and operationalize data governance platforms (e.g., metadata management tools, data profiling, cataloging, and monitoring technologies).
• Implement automated data quality validation, monitoring, and reporting capabilities.

Operationalization of Data Governance

• Translate approved data governance strategies into executable, day‑to‑day operational practices for AO staff and systems.
• Develop and document repeatable processes for data handling, privacy, management, and quality control.
• Establish workflows governing data access requests, approvals, and escalations.
  Assign clear responsibilities across data owners, stewards, custodians, and users for monitoring, reporting, and ensuring compliance.
• Integrate governance policies directly into daily operations and system workflows, including automation of data validation and quality checks.
• Gather feedback, assess effectiveness, and refine governance processes continuously.

Data Governance Change Management

• Execute change management strategies addressing people, processes, and culture to ensure sustainable adoption of data governance practices.
• Develop training modules that explain the benefits of CMM data standards and the mechanics of the data governance program, including learning objectives, illustrative content, and self-assessment questions for AO and local court staff.
• Create stakeholder communication strategies using multiple channels (email, meetings, dashboards) tailored to diverse user groups.
• Promote and reinforce a data-driven culture emphasizing accountability, quality, and responsible data use; refine policies, training, and communications based on adoption trends and AO input.
• Update change management plans throughout the period of performance as governance structures evolve.
• Provide recommendations for applying human-centered design principles to data elements captured and tracked in CMM.

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).
• Demonstrated experience leading enterprise data governance programs.
• Experience translating governance policy into practical operational processes in delivery environments.
• Strong understanding of data quality management, metadata practices, and stewardship models.
• Experience governing high-sensitivity or regulated data with clear compliance expectations.
• Experience with data quality profiling and monitoring techniques and common tooling patterns.
• Experience defining and governing enterprise data standards across multiple teams and delivery pods.
• Strong background in data modeling, integration patterns, and change data capture concepts.
• Experience with metadata and catalog tools such as Collibra, Alation, or Qlik.
• Practical experience implementing glossary and lineage capabilities in modern data platforms.
• Ability to translate technical metadata into business-friendly definitions and documentation.
• Experience implementing data privacy controls in regulated or high-sensitivity environments.
• Experience with access management and operationalizing privacy requirements.
• Experience partnering with security, governance, and engineering teams to implement compliant data sharing.