Data Governance Architect

Role Purpose The Data Governance Consultant is responsible for assessing, defining, and operationalizing enterprise data governance across multiple data domains. The role emphasizes governance frameworks, policies, operating models, and adoption—ensuring that data is trusted, compliant, and consistently used across the organization. Key Responsibilities Current State (As Is) Governance Assessment Data ownership, stewardship, and accountability models Business glossary, metadata, and lineage practices Data quality management approaches Privacy, security, and retention controls Assess maturity by comparing current practices against industry best practices, recognized governance frameworks (e.g., DAMA, federated governance models), and regulatory expectations Identify gaps in governance coverage, consistency, and execution Governance Framework & Best Practice Recommendations Define and recommend a future-state governance framework, including governance operating model (central, federated, or hybrid) Define clear roles, RACI, and stewardship responsibilities Set standards for data definitions, quality, and lifecycle management Propose best practice governance processes based on prior enterprise implementations, tailored to organizational culture and maturity Governance Technology Enablement Advise on selection and use of data governance and catalog platforms (e.g., business glossary, metadata, lineage, policy management) Define how governance processes and policies should be operationalized through tools and workflows Ensure governance is embedded into day‑to‑day data and analytics activities Roadmap, Prioritization & Change Enablement Drive development of a long‑term data governance roadmap, detailing target capabilities and maturity milestones, prioritized initiatives with sequencing and dependencies, and quick wins versus foundational improvements Support change management and adoption by defining rollout and enablement strategies and aligning governance with business value and regulatory outcomes Expected Outcomes Clear understanding of current governance maturity and gaps Pragmatic, business‑aligned governance framework Improved trust, consistency, and compliance across data domains Scalable governance model that supports analytics and AI adoption #J-18808-Ljbffr Programmers.io