Enterprise Data Governance Consultant - Hybrid Nashville, TN

Novalink Solutions LLC•Nashville, TN

1d•Hybrid

About The Position

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. This contractor position will work under the direction of the Enterprise Data Governance Manager helping 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. The State’s Enterprise Data Governance Program is built around a coordinated Framework, Guidebook, and Playbook that define the “why,” “what,” and “how” of statewide data governance implementation. This position is intended for a consultant with strong public-sector facilitation, AI governance, change management, training, communications, and data governance implementation skills. The consultant will help translate governance concepts into practical agency actions, including data strategy development, governance meeting facilitation, stakeholder engagement, maturity assessments, implementation planning, training delivery, and program communications.

Requirements

Facilitate cross-functional meetings with business, technology, privacy, security, legal, compliance, and executive stakeholders.
Develop practical data governance strategies, implementation plans, training plans, communications, and adoption materials.
Translate complex data governance, data management, metadata, data quality, privacy, and AI governance concepts into plain language.
Build trust with agency stakeholders and guide groups toward decisions, documented actions, and measurable progress.
Apply change management practices to support adoption of new roles, responsibilities, processes, and governance behaviors.
Develop business value cases for data governance initiatives.
Support governance documentation aligned to frameworks, policies, procedures, standards, controls, and audit expectations.
Understand data governance operating models, data ownership, data stewardship, metadata, data catalogs, data quality, data lifecycle management, data sharing, and data risk management.
Work independently while coordinating with the Enterprise Data Governance Manager, Data Governance Analyst, and agency stakeholders.
Produce clear, professional, executive-ready written products.

Nice To Haves

Experience supporting data governance, data management, enterprise information management, organizational change management, training, or stakeholder engagement programs.
Experience working with state government, local government, public-sector programs, or highly regulated environments.
Familiarity with DAMA-DMBOK, data stewardship, metadata management, data quality management, data classification, data lifecycle management, and data governance maturity models.
Familiarity with AI governance concepts, responsible AI principles, or frameworks such as the NIST AI Risk Management Framework.
Experience developing and delivering training, workshops, presentations, job aids, communications, and adoption campaigns.
Experience supporting governance councils, committees, working groups, or cross-functional decision-making bodies.
Experience with enterprise data catalog, metadata, business glossary, data inventory, issue tracking, collaboration, or knowledge management tools.
Management, PMP, CISA, CIPM, or related credentials.
Relevant certifications are desirable but not required, such as CDMP, Prosci/Change

Responsibilities

Support agency awareness of AI governance concepts, including ethical, transparent, explainable, accountable, and human-reviewed use of data and AI-enabled systems.
Help document AI-related data use cases, data sources, stewardship responsibilities, risk considerations, and governance checkpoints.
Coordinate with appropriate privacy, security, legal, records, and compliance stakeholders when governance activities involve sensitive, confidential, regulated, or high-risk data.
Facilitate agency exploitation of AI technologies to establish practitioners to automate and/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, including HIPAA, FERPA, CJIS, IRS Pub. 1075, PCI, FTI, PII, and other applicable standards when relevant to agency operations.
Support agency data governance planning, including charters, roadmaps, operating models, stakeholder maps, and implementation plans.
Assist agencies in defining data governance scope, ownership, roles, responsibilities, decision rights, and engagement processes.
Help identify agency value-based business needs, data pain points, data quality risks, and opportunities for improved data sharing and reuse.
Support agency maturity assessments and develop practical work plans to close governance gaps.
Translate technical data governance concepts into plain-language guidance suitable for executives, business program staff, data stewards, and operational teams.
Promote consistent use of Tennessee’s eight core data governance elements: Organization, Policies, Procedures, Standards/Definitions, Architecture, Data Admin/Controls, Metrics/Reporting, and Audits.
Help agencies complete governance artifacts such as RACI charts, business glossaries, data dictionaries, data inventories, data issue logs, policy/procedure mappings, stewardship plans, and governance roadmaps.
Support documentation of data domains, data owners, data stewards, business definitions, data flows, data quality rules, risks, controls, and metrics.
Assist agencies with Playbook-aligned implementation activities and evidence gathering for audit readiness.
Coordinate with the Data Governance Analyst on catalog, metadata, data classification, lineage, and related documentation needs.
Support agency use of governance metrics and maturity indicators to monitor progress and demonstrate business value.
Maintain organized repositories of governance artifacts, meeting records, training materials, communications, and implementation evidence.
Plan, facilitate, and document agency data governance meetings, workshops, steering committee sessions, 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.
Support resolution of cross-functional data issues by clarifying decision points, documenting options, identifying risks, and escalating unresolved matters.
Help agencies operationalize governance committees and recurring governance cadences consistent with statewide guidance.
Support business value case development for data governance initiatives, including benefits, risks, resource needs, expected outcomes, and implementation options.
Develop and execute stakeholder engagement and change management plans for agency data governance adoption.
Create communication products such as briefings, talking points, newsletters, intranet content, FAQs, one-page summaries, presentations, and adoption messaging.
Promote data governance as a business-enabling capability, not only a compliance activity.
Communicate the value of data governance in terms of trusted data, reduced risk, improved service delivery, better decision-making, and increased efficiency.
Support messaging for managing data as an enterprise asset, consistent with Tennessee’s data governance policy principles. The Guidebook states that data is recognized as a valued and strategic enterprise asset and that accountability, quality, and compliance must be clearly defined and managed.
Identify adoption barriers and recommend interventions such as targeted communications, leadership briefings, training refreshers, job aids, and facilitation support.
Develop training plans, course outlines, instructor-led materials, self-service learning content, quick reference guides, and role-based learning paths.
Deliver training for data owners, data stewards, data custodians, data producers, data consumers, and agency governance teams.
Support data fluency training aligned to Tennessee’s enterprise data governance methodology, tools, and templates.
Create practical exercises using agency-relevant examples such as data ownership, business glossary terms, data quality dimensions, data classification, data sharing, metadata, and governance meeting practices.
Coordinate training feedback, attendance, adoption metrics, and improvement recommendations.
Reinforce data quality expectations, including accuracy, timeliness, accessibility, completeness, and consistency. Tennessee’s Guidebook identifies these as five critical data quality dimensions.