Data Governance Lead
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- Establish ownership, policy and a discoverable inventory of enterprise data
- Make governance operational through quality, reference data and controls
- Automate policy and govern data for AI, analytics and high-trust systems
Benchmark: OpenAI Privacy Engineering + Amazon enterprise data strategy + modern lakehouse governance roles (Sep 2026): make data discoverable, owned, trustworthy and policy-aligned through inventory/catalog, classification, lineage, stewardship, quality, master/reference data, access and retention; translate policy into enforceable controls and extend unified governance to models, RAG, MCP and agents. Mastery ladder: 2 job-market competencies per level; 2 direct VIDEO bridges per competency (12 total).
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Establish ownership, policy and a discoverable inventory of enterprise data
Governance operating model, stewardship + accountable ownership
Coverage: Data Governance / Operating Models / Stewardship / Policy
Catalog, metadata, lineage + classification
Coverage: Data Catalog / Metadata / Lineage / Classification / Discovery
Make governance operational through quality, reference data and controls
Data quality, observability + enforceable data contracts
Coverage: Data Quality / Observability / Contracts / SLOs
Master/reference data, semantics + knowledge models
Coverage: MDM / Reference Data / Ontologies / Knowledge Graphs
Automate policy and govern data for AI, analytics and high-trust systems
RBAC/ABAC, policy-as-code + auditability
Coverage: Access Governance / ABAC / Policy as Code / Audit Controls
AI-ready governance, semantic metadata + governed AI access
Coverage: AI Governance / Semantic Metadata / RAG / Agent Data Controls
Role-Readiness Proof / Capstone
Design an enterprise data-governance operating system: domains, owners and stewards; catalog/classification; critical-data elements; lineage; quality rules and SLOs; issue workflow; master/reference data; certification; RBAC/ABAC and policy controls; retention and audit evidence; semantic/knowledge context for AI; governance council decision rights; adoption and trust scorecard.
Proof Rubric
- Make ownership and decision rights explicit
- prove discoverability and lineage
- define measurable quality
- enforce policy at access and lifecycle boundaries
- keep exceptions auditable
- standardize reference/semantic meaning
- support unstructured and AI-context data
- show governance improving reuse, risk control and time-to-trust