Enterprise Data Governance Consultant

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Role: Enterprise Data Governance Consultant

Location: Nashville, TN || Hybrid

Duration:12 Months

Number of Positions: 5

Position Overview
The Enterprise Data Governance Consultant will support the State of Tennessee Center for Enterprise Data & Analytics (CEDA) in expanding enterprise data governance services, AI data preparations, training, communications, stakeholder engagement, and agency implementation support.
Working under the direction of the Enterprise Data Governance Manager, the consultant will help agencies and departments establish, mature, and sustain data governance programs.
The role supports Tennessee's enterprise approach to managing data as a strategic asset, improving trusted data use, reducing risk, enabling secure data sharing, and increasing efficiency through standardization.
This position requires strong public-sector facilitation, AI governance, change management, training, communications, and data governance implementation skills.
Key Responsibilities
AI Governance, Privacy, Risk & Compliance
Support agency awareness of responsible AI governance concepts, including ethical, transparent, explainable, accountable, and human-reviewed use of data and AI-enabled systems.
Document AI-related data use cases, data sources, stewardship responsibilities, risk considerations, and governance checkpoints.
Coordinate with privacy, security, legal, records, and compliance stakeholders involving sensitive, confidential, regulated, or high-risk data.
Support the use of AI technologies to automate or streamline data governance practices and artifacts.
Reinforce requirements for data classification, access management, data minimization, authorized use, retention, and secure data sharing.
Support documentation of data-related risks, issues, policy exceptions, remediation actions, and audit evidence.
Promote appropriate safeguards for protected or regulated data.
Data Governance Strategy & Implementation
Support agency data governance planning, including charters, roadmaps, operating models, stakeholder maps, and implementation plans.
Assist agencies in defining governance scope, ownership, roles, responsibilities, decision rights, and engagement processes.
Identify business needs, data pain points, data-quality risks, and opportunities for improved data sharing and reuse.
Conduct or support governance maturity assessments and develop practical work plans to address gaps.
Translate technical data-governance concepts into plain-language guidance for executives, business teams, data stewards, and operational teams.
Help develop governance artifacts including RACI charts, business glossaries, data dictionaries, data inventories, issue logs, stewardship plans, and governance roadmaps.
Document data domains, owners, stewards, business definitions, data flows, data-quality rules, risks, controls, and metrics.
Support governance metrics and maturity indicators.
Facilitation & Stakeholder Engagement
Plan, facilitate, and document data-governance meetings, workshops, steering committees, and stewardship working groups.
Prepare agendas, meeting materials, decision logs, action-item trackers, issue logs, and executive-ready summaries.
Facilitate discussions among data owners, data stewards, business leaders, technology teams, privacy, security, legal, and compliance stakeholders.
Help resolve cross-functional data issues by clarifying decisions, documenting options, identifying risks, and escalating unresolved matters.
Support business-value cases for data-governance initiatives.
Change Management & Communications
Develop and execute stakeholder-engagement and change-management plans.
Create briefings, talking points, newsletters, intranet content, FAQs, one-page summaries, presentations, and adoption messaging.
Communicate the value of data governance in terms of trusted data, reduced risk, improved service delivery, better decision-making, and increased efficiency.
Identify adoption barriers and recommend appropriate interventions.
Training
Develop training plans, course outlines, instructor-led materials, self-service learning content, quick-reference guides, and role-based learning paths.
Deliver training to data owners, data stewards, data custodians, data producers, data consumers, and agency governance teams.
Develop practical exercises covering data ownership, business glossaries, data quality, data classification, data sharing, metadata, and governance practices.
Track training feedback, attendance, adoption metrics, and improvement recommendations.
Required Knowledge, Skills & Abilities
Ability to facilitate cross-functional meetings involving business, technology, privacy, security, legal, compliance, and executive stakeholders.
Ability to develop practical data-governance strategies, implementation plans, training plans, communications, and adoption materials.
Ability to translate complex data governance, data management, metadata, data quality, privacy, and AI governance concepts into plain language.
Strong stakeholder-engagement and facilitation capabilities.
Change-management experience supporting adoption of new roles, responsibilities, processes, and governance behaviors.
Understanding of data governance operating models, data ownership, stewardship, metadata, data catalogs, data quality, data lifecycle management, data sharing, and data-risk management.
Ability to develop business-value cases for data-governance initiatives.
Ability to work independently while coordinating with data-governance leadership and agency stakeholders.
Ability to produce professional, executive-ready written materials.
Preferred Qualifications
Experience with data governance, data management, enterprise information management, organizational change management, training, or stakeholder-engagement programs.
Public-sector, government, or highly regulated industry experience.
Familiarity with DAMA-DMBOK.
Familiarity with data stewardship, metadata management, data-quality management, data classification, data lifecycle management, and data-governance maturity models.
Familiarity with AI governance, responsible AI principles, or frameworks such as the NIST AI Risk Management Framework.
Experience developing and delivering training, workshops, presentations, job aids, communications, or adoption campaigns.
Experience supporting governance councils, committees, working groups, or cross-functional decision-making bodies.
Experience with enterprise data catalogs, metadata, business glossaries, data inventories, issue tracking, collaboration, or knowledge-management tools.