What you’ll do

• Data Governance operating model: Define and maintain the governance framework (domains, councils/forums, decision rights, RACI), clarifying roles such as Data Owners, Data Stewards, and technical custodians. Facilitate governance cadences (domain working groups, escalation paths, prioritization) and drive stakeholder alignment across business and tech.
• Own enterprise metadata: Govern and scale Business Glossary, KPI/metric definitions, data dictionaries, and documentation standards to reduce ambiguity and improve data literacy. Drive adoption of a data catalog approach (discovery, context, ownership, certifications) and ensure assets have the right business and technical metadata.
• Establish standards and processes for data lineage (business + technical): certification of critical datasets/reports, and impact analysis for changes. Define governance requirements for new data products (documentation, ownership, SLAs, access model, retention, quality expectations, monitoring).
• Data quality as strategic pillar: Define DQ strategy for critical domains: quality dimensions, thresholds, ownership, and remediation workflows. Drive root-cause analysis patterns with platform/engineering teams and track improvements via KPIs. (Stewardship typically covers day-to-day quality management, within a broader governance model.)
• Enablement, change management: Create playbooks, templates, and training to embed governance in delivery (from intake to release). Mentor more junior profiles and act as a trusted advisor for business stakeholders, helping teams “do the right thing” with minimal friction.