Data Governance Training Coordinator Richmond, VA

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Job Summary
The Data & AI Governance Training Coordinator is a subject matter expert responsible for designing developing and delivering enterprise training and enablement programs that support adoption of data governance and AI governance capabilities. This role ensures that governance frameworks policies tools and workflows are clearly understood and consistently applied across business units technology teams and stakeholders. The position partners closely with Data Governance Data Risk Data Quality AI Governance and Program Management to translate complex governance concepts into clear accessible training guidance and enablement materials. The role is accountable for improving governance adoption strengthening data literacy and enabling teams to effectively engage with governance processes tools and responsibilities.
Key Responsibilities includes define and execute the enterprise training and enablement strategy for Data & AI Governance. Develop role-based training programs aligned to governance functions (e.g. stewards data owners engineers analysts business users). Align training content with governance frameworks policies and operational workflows. Create training materials including presentations guides SOPs job aids and e-learning modules. Translate complex governance risk and AI concepts into clear actionable learning content. Maintain centralized training repositories templates and reusable materials. Deliver training sessions workshops onboarding sessions and governance briefings. Support onboarding of new teams domains and stakeholders into governance processes. Facilitate working sessions to reinforce adoption of governance tools and workflows. Drive enterprise adoption of governance practices through structured training and communications. Partner with Program Manager and leadership to align enablement with rollout timelines and initiatives. Support change management efforts including awareness campaigns and stakeholder engagement. Define and track metrics for training effectiveness and governance adoption (e.g. completion rates engagement process adherence). Gather feedback from stakeholders to improve training content and delivery methods. Continuously enhance training programs based on evolving governance maturity and needs. Partner with Data Governance Data Risk Data Quality AI Governance and technical teams to ensure training reflects current processes and tools. Align training with catalog data quality risk and AI governance workflows to ensure consistency. Act as a bridge between governance design and enterprise execution.