About the Role:
Client advises customers on the people-and-process work that makes Data and AI Governance real. That work has to land on the ground, inside business domains, where governance is actually practiced. The Data Governance Consultant is a hands-on practitioner who works across domains to implement governance programs designed by the client project team and Data Governance Lead.
Data Governance Consultants operationalize stewardship models, run domain-level discovery and prioritization, drive policy adoption, and serve as the connective tissue between strategy and execution.
Key Responsibilities:
- Domain Implementation: Implement governance frameworks (decision rights, stewardship, policies) within specific business domains: finance, customer, product, supply chain, HR, and others.
- Stakeholder Engagement: Run workshops, interviews, and working sessions with business and IT stakeholders to surface requirements, build consensus, and drive adoption.
- Stewardship Operationalization: Identify and onboard data stewards, document role responsibilities, and coach stewards through their first cycles of governance activity.
- Policy Drafting & Adoption: Translate enterprise governance policies into domain-specific procedures; drive adoption through training, documentation, and active facilitation.
- Use Case Delivery: Lead governance use cases end-to-end (issue management, data quality remediation, glossary curation, access reviews) and document the patterns for reuse.
- Metadata Contribution: Partner with the Metadata Governance Lead to populate business glossary, data dictionary, and lineage content for the domains you cover.
- AI Readiness: Assess domain data against the requirements of AI/ML use cases; prioritize the governance work that makes domain data trustworthy for AI consumption.
- Deliverable Production: Produce high-quality deliverables (assessments, roadmaps, runbooks, training materials, presentations) that meet client's standards.
- Knowledge Transfer: Build the client capability so the governance program continues to mature beyond the engagement.
Required Qualifications:
- 5+ years of data governance, data management, or business analysis experience, ideally including consulting.
- Hands-on experience operationalizing governance programs.
- Strong collaboration skills with business and IT stakeholders at multiple levels of seniority.
- Experience working across multiple data domains and the ability to ramp quickly into unfamiliar subject matter.
- Excellent written and verbal communication; ability to produce client-ready deliverables.
Preferred Qualifications:
- Strong facilitation skills with business and IT stakeholders at multiple levels of seniority
- Familiarity with how AI/ML workflows consume domain data and the governance controls required to make that data trustworthy.
- Experience with one or more catalog/governance platforms (tool-agnostic we look for transferable expertise).
- Familiarity with frameworks such as DAMA-DMBOK, DCAM, or EDM Council CDMC.
- Industry experience in life sciences, financial services, healthcare, or other regulated environments.
- CDMP, IQCP, or equivalent credentials.
What Success Looks Like:
By the end of an engagement the Data Governance Consultant will have:
- Completed domain-level discovery, requirements gathering, and prioritization output for the assigned domain(s).
- Translated enterprise frameworks into domain-specific operating procedures and runbooks.
- Operationalized governance within the assigned domain(s), including activating stewards, guiding policy adoption, and establishing a sustainable governance cadence; delivered assigned use cases (issue management, glossary curation, quality remediation).
- Surfaced and prioritized the governance work required to support AI/ML use cases in the domain.
- Built a measurable client capability that sustains the program post-engagement; produced a body of deliverables that meets Client's quality bar.