The Governance & Information Data Domain Partner serves as the primary governance point of contact for assigned functional domains and strategic initiatives across Data Governance, Information Management, and AI Governance. The partner identifies requirements, coordinates the appropriate teams, and ensures agreed activities have clear owners, timelines, and follow-through. The partner supports execution, tracks progress, addresses coordination gaps, and escalates barriers so governance activities are completed by the responsible teams.

This role is accountable for effective domain engagement, coordination, visibility, and follow-through. Business owners and capability teams retain accountability for decisions and execution within their respective areas.

Success requires strong relationship-building and facilitation skills, business and technical fluency, sound judgment, and the ability to influence without direct authority. The Domain Partner may support multiple functional domains, such as Finance, Supply Chain, Procurement, and Customer Care, with assignments prioritized by Governance Integration Office leadership in partnership with capability leaders.

Key Responsibilities

Domain Partnership and Engagement

• Serve as the primary Governance and Information partner for assigned domains, providing a consistent point of contact across Data Governance, Information Management, and AI Governance.
• Build trusted relationships with business leaders, Data Owners, Data Stewards, business process owners, AI business and technical owners, and other key stakeholders.
• Partner with AAD Product Management and Engineering to align governance engagement with business priorities and technology delivery.
• Develop an understanding of each assigned domain’s business processes, data, systems, information needs, AI use, priorities, and challenges.
• Maintain awareness of current and planned initiatives to identify governance and information needs early.
• Help stakeholders understand applicable requirements, available capabilities, and their ownership and decision-making responsibilities.
• Promote governance and information practices as practical ways to improve business outcomes, support trusted data, and enable responsible AI adoption.

Intake, Coordination, and Initiative Support

• Work within the Governance Integration Office intake process to understand domain requests, clarify business needs, and identify the appropriate capability teams and stakeholders.
• Provide coordinated governance representation for complex initiatives, including ERP transformations, system implementations, data migrations, analytics and AI programs, and data platform transformations.
• Engage throughout the initiative lifecycle, from intake and planning through design, implementation, readiness, and transition to ongoing operations.
• Work with capability specialists to identify applicable requirements, deliverables, dependencies, risks, and review needs.
• Partner with project and program managers to incorporate agreed governance activities and milestones into broader delivery plans.
• Coordinate cross-functional participation and maintain clear handoffs between business teams, project teams, and governance capabilities.
• Track assigned activities, dependencies, risks, issues, and decisions, and communicate progress and unresolved needs to stakeholders.
• Facilitate required reviews and approvals, ensuring decisions reach the appropriate owners.
• Escalate unresolved ownership, priority, resource, or governance issues through Governance Integration Office leadership and the appropriate capability leaders.
• Confirm that agreed activities have designated owners and timelines, monitor progress through completion, and follow up or escalate when commitments are at risk.

Data Governance Support

• Facilitate the identification and confirmation of Data Owners and Data Stewards and help clarify their responsibilities.
• Support business teams in identifying and documenting critical data elements and other high-value data assets.
• Help teams identify and address applicable data ownership, quality, access, and governance requirements.
• Coordinate with Data Quality specialists and business stakeholders to define quality expectations, document issues, and support remediation planning and follow-through.
• Support data access requests by helping teams clarify purpose, identify the appropriate Data Owners, and navigate the established approval process.
• Support data readiness and migration activities by ensuring governance needs and ownership decisions are addressed.
• Support adoption of enterprise Data Governance policies, standards, workflows, and tools.

Information Management Support

• Partner with Information Management to help domains organize and describe their information so it can be understood and reused by people and AI.
• Facilitate the development and maintenance of business definitions, glossary content, metadata, and relationships between business concepts and data assets.
• Help domain stakeholders identify authoritative information sources and clarify inconsistent definitions or terminology.
• Coordinate domain participation in data catalog, semantic data, ontology, knowledge graph, and context layer initiatives.
• Gather business context and requirements for Information Management specialists and support validation of resulting definitions, mappings, and relationships.
• Support domain adoption and maintenance of catalog and metadata content in accordance with enterprise standards.
• Help business owners and stewards fulfill their responsibilities for the accuracy and currency of domain content.

AI Governance Support

• Help domains identify AI use that requires engagement with the enterprise AI Governance process.
• Support identification of accountable AI business owners and responsible technical owners, as applicable.
• Help teams document intended use, business context, affected processes, data dependencies, and other information needed for intake and review.
• Coordinate domain participation in AI intake, inventory, assessments, specialist reviews, and lifecycle activities.
• Work with AI Governance Operations, Responsible AI and Assurance, and relevant specialist functions to clarify requirements, evidence needs, and next steps.
• Track assigned actions, review conditions, remediation commitments, and material changes that may require further review.
• Help stakeholders understand when AI concerns, exceptions, or unresolved risks need to be escalated.
• Support adoption of approved AI Governance practices while preserving the decision authority of business owners and specialist functions.

Cross-Functional Collaboration and Continuous Improvement

• Connect business stakeholders with Data Governance, Information Management, AI Governance, Product Management, Engineering, and other relevant partners.
• Translate business needs into clear governance and information requirements and explain technical considerations in language stakeholders can act upon.
• Facilitate discussions where stakeholders have differing perspectives on ownership, definitions, requirements, risks, or priorities.
• Influence outcomes through credibility, trusted relationships, and alignment around shared business objectives.
• Navigate competing priorities and organizational complexity while maintaining clear expectations and constructive relationships.
• Coach owners, stewards, and other stakeholders in applying established practices and using available capabilities.
• Share recurring domain needs, lessons learned, and improvement opportunities with Governance Integration Office and capability leaders.
• Contribute reusable approaches that improve consistency, reduce unnecessary effort, and strengthen domain engagement.

Required

• Bachelor’s degree or an equivalent combination of education and relevant professional experience.
• 4–6 years of relevant experience in Data Governance, information or data management, business analysis, project delivery, technology, or related disciplines.
• Working knowledge of Data Governance practices, including ownership, stewardship, data quality, metadata, and policies and standards.
• Understanding of how business definitions, metadata, and information context support analytics, technology delivery, and AI.
• Demonstrated experience supporting complex, cross-functional projects or transformation initiatives.
• Strong organizational and coordination skills, with the ability to coordinate multiple stakeholders, activities, dependencies, and priorities.
• Demonstrated ability to build trusted relationships and influence stakeholders without direct authority.
• Strong facilitation skills, including the ability to guide discussions toward clear requirements, ownership, decisions, and next steps.
• Professional proficiency in English and excellent written and verbal communication skills with business and technical audiences.
• Ability to translate between business requirements, data and information concepts, and technical considerations.
• Sufficient technical fluency to work effectively with Product Management, Engineering, architecture, and other technology teams.
• Ability to work independently within established frameworks, recognize when specialist input is needed, and escalate issues appropriately.
• Sound judgment and a collaborative, practical approach to balancing governance requirements with business and delivery needs.

Preferred

• Experience working in an enterprise governance, information management, or data management program.
• Experience supporting data migrations, analytics or AI programs, or enterprise data platform transformations.
• Experience working with Data Owners and Data Stewards in a federated or domain-oriented governance model.
• Experience with data catalogs, business glossaries, or metadata management.
• Experience with technologies such as data.world, Experian Aperture Data Studio, Databricks, or similar platforms.
• Familiarity with data models, integrations, APIs, data pipelines, or modern enterprise data platforms.
• Experience facilitating adoption, training stakeholders, or coaching others in governance and information practices.

Measures of Success

• Strong, trusted relationships with domain stakeholders and Product Management and Engineering teams.
• Early identification of governance and information needs and timely engagement of the appropriate specialists.
• Clear, accepted handoffs between teams, with ownership and next steps understand across delivery stages.
• Effective follow-through that ensures responsible teams complete agreed governance activities, with timely escalation of barriers that could affect delivery .
• Accurate, timely visibility into progress, dependencies, risks, issues, and decisions.
• Improved domain participation in data ownership, stewardship, data quality, metadata, and information management practices.
• Timely progression of AI intake, ownership documentation, reviews, and follow-up actions through effective coordination with responsible teams.
• Increased stakeholder understanding and adoption of enterprise governance capabilities.
• Positive stakeholder feedback on the partner’s ability to simplify engagement, resolve coordination gaps, and support successful business outcomes.