Data Governance & AI Governance Lead
Location: Dallas, TX
Onsite Requirements: Hybrid - onsite 3 days per week
Contract: 6 months
Compensation: $65-70/hr

Introduction
We are seeking a Data Governance & AI Governance Lead to help establish and operationalize an enterprise-wide data governance program from the ground up. This role will partner closely with Security, IT, business stakeholders, data owners, and technical teams to understand the organization's data landscape, establish governance standards, improve data discoverability and protection, and create the foundational processes needed to support the responsible use of data and emerging AI technologies.
The ideal candidate brings hands-on experience developing or implementing data governance programs, including data ownership, stewardship, policies, metadata, business glossaries, data dictionaries, governance frameworks, and accountability models. Experience with AI governance is valuable but not required; the successful candidate should have an interest in learning and helping the organization establish governance practices that support the safe and responsible adoption of AI.
Day-to-Day Responsibilities
Data Governance Program Development

• Help lead the development and implementation of an enterprise data governance program, including governance structures, processes, standards, and operating practices.
• Partner with Security and IT to develop a clear understanding of the organization's data landscape, including key data sources, systems, data types, and areas of sensitivity.
• Identify and engage business and technical data owners across the organization.
• Establish and facilitate a cross-functional Data Governance Working Group consisting of data owners and other key stakeholders.
• Define and help implement a data stewardship model, including identification of data stewards responsible for the day-to-day management and quality of data.
• Develop governance charters, operating models, RACI matrices, roles, responsibilities, and accountability frameworks.

• Partner with Security and technology teams to expand data discovery and classification capabilities across the enterprise.
• Participate in governance activities surrounding tools such as Microsoft Purview, Varonis, or similar data discovery and classification technologies; direct hands-on tool administration is not required.
• Establish processes for identifying, classifying, protecting, and managing sensitive data, including PII, PHI, financial, confidential, and other regulated or sensitive information.
• Define governance requirements around data access, protection, retention, and deletion.
• Identify gaps in the organization's data governance and data protection processes and help drive remediation.

• Establish standards and processes for enterprise metadata management and data discoverability.
• Develop and maintain business glossaries, data dictionaries, data catalogs, and data definitions.
• Work with data owners and subject matter experts to establish consistent definitions, ownership, lineage, and usage guidelines for critical data.
• Define data governance metrics and reporting to measure adoption, compliance, data quality, and program effectiveness.

• Establish foundational data governance practices necessary to support the organization's expanding use of AI.
• Partner with stakeholders to ensure AI initiatives incorporate appropriate data governance, classification, access, privacy, security, and usage considerations.
• Identify governance requirements for AI tools and use cases as the organization's AI program evolves.
• Participate in the development of emerging AI governance policies, standards, review processes, and responsible-use practices.
• Collaborate with Security, IT, Legal/Compliance, and business stakeholders to identify potential data risks associated with AI adoption.
• Stay current on emerging data and AI governance practices and help translate them into practical enterprise processes.

• Build relationships with data owners, data stewards, Security, IT, business leaders, and other stakeholders to drive adoption of governance practices.
• Work collaboratively with internal change management, communications, and organizational effectiveness teams to support implementation and adoption.
• Communicate complex data governance concepts in a practical and understandable manner to both technical and non-technical audiences.
• Facilitate workshops, working sessions, stakeholder meetings, and governance forums.
• Help drive organizational adoption of new policies, processes, standards, and governance responsibilities.

• Enterprise Data Governance Charter
• Data Governance Operating Model
• Data Owner and Data Steward Framework
• Data Governance Working Group
• Data Governance RACI
• Enterprise Data Governance Policies & Standards
• Data Classification & Protection Standards
• Data Access Governance Practices
• Data Retention & Deletion Guidelines
• Metadata Management Framework
• Business Glossary & Data Dictionary
• Data Catalog & Discoverability Practices
• Governance Metrics & Reporting
• Data Governance Roadmap
• AI Governance Framework and supporting policies as the program matures

• 5+ years of experience in data governance, data management, information governance, data quality, or a closely related discipline.
• Demonstrated experience helping to establish, implement, or mature a data governance program or framework using industry best practices.
• Familiarity with Microsoft Purview, Varonis, or similar data discovery/classification platforms; hands-on Varonis administration is not required.
• Experience defining and implementing data ownership and stewardship models.
• Experience developing data governance policies, standards, procedures, RACI models, charters, or operating frameworks.
• Experience with metadata management, business glossaries, data dictionaries, data catalogs, or data classification.
• Understanding of data privacy, protection, access, retention, and deletion concepts.
• Strong experience working across Security, IT, business/data owners, and other cross-functional stakeholders.
• Strong facilitation, communication, documentation, and stakeholder-management skills.
• Ability to operate in an environment where the governance program is still being defined and processes are not yet fully established.
• Experience with data catalogs, metadata management, data lineage, or enterprise data management platforms.
• Self-driven and curious by nature, with the ability to work independently, identify gaps, and help determine what needs to be built next.

• Experience with AI governance, responsible AI, or AI risk management.
• Experience working with sensitive or regulated data such as PHI, PII, financial, or confidential information.
• Familiarity with AI/ML, generative AI, or enterprise AI adoption.
• Experience developing governance metrics, dashboards, or program reporting.
• Experience working with organizational change management or adoption teams.