Key responsibilities
- Design and operationalize the enterprise data governance framework — including policies, standards, data ownership models, and stewardship councils — aligned with business strategy and regulatory requirements.
- Define and enforce data quality dimensions (accuracy, completeness, consistency, timeliness, validity) across critical data domains, and own the DQ metrics and reporting dashboard.
- Lead the implementation and ongoing management of the data catalog, business glossary, and data lineage capabilities to support self-service and data discoverability.
- Partner with legal, compliance, and risk teams to ensure data practices adhere to GDPR, CCPA, HIPAA, and internal data privacy policies.
- Establish and chair the Data Governance Council, facilitating cross-functional working groups to resolve data issues, prioritize initiatives, and drive accountability among data owners and stewards.
- Collaborate with data engineering and platform teams to embed automated data quality checks, validation rules, and alerting into data pipelines and ingestion workflows.
- Drive cultural change by delivering training programs, playbooks, and enablement resources that build data literacy and governance awareness across all business functions.
- Manage and mentor a team of data stewards and data quality analysts, setting objectives, conducting reviews, and fostering a high-performance team culture.
Required:
- 8+ years in data management, with at least 3 years leading data governance or data quality programs.
- Proven experience building governance operating models including policies, stewardship structures, and data ownership frameworks from the ground up.
- Hands-on experience with data catalog and governance tools (e.g., Collibra, Alation, Atlan, Purview, or equivalent).
- Strong knowledge of data quality frameworks, DQ dimensions, and profiling/monitoring tools (e.g., Great Expectations, dbt tests, Monte Carlo, Soda).• Excellent communication and facilitation skills, with a track record of driving alignment across technical and non-technical stakeholders.
- Familiarity with data privacy regulations (GDPR, CCPA) and their practical implications for data governance.
Preferred:
- CDMP (Certified Data Management Professional) or equivalent DAMA certification.
- Experience in cloud-native data environments (AWS, Azure, GCP) and modern data stack (dbt, Snowflake, Databricks, or similar).
- Exposure to MDM, data mesh, or data fabric concepts and how governance integrates across these paradigms.
- Background in regulated industries such as financial services, healthcare, or life sciences where data compliance is mission-critical.
- Experience with SQL and Python for data profiling and quality automation.