Lead Enterprise Data Governance Professional

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The Lead, Enterprise Data Governance Professional is responsible for implementing, operating, and maturing the Integrated Business Advancement organization’s data governance program. This role applies advanced expertise to ensure consistent data quality, trustworthy data usage, and adherence to enterprise data standards. The Lead works on complex issues with moderate to substantial scope, exercises independent judgment, and operates with minimal supervision. This position also serves as a technical resource for enterprise data platforms while providing training and guidance to Data Stewards.

The Lead, Enterprise Data Governance Professional provides oversight of data usage, data quality, system analysis, and data retention policies to ensure robust and compliant data management practices across the organization. This role collaborates across business units, technology teams, and leadership stakeholders to promote data consistency, accuracy, and alignment with enterprise objectives.

Key responsibilities include contributing to the development of data governance policies, standards, and best practices while maintaining documentation and metrics that monitor governance effectiveness. The Lead supports intake triage for new projects, ensuring appropriate stewardship assignment and completion of required documentation before and after go-live events.

This individual develops best practices for new tools that integrate with enterprise datasets and provides subject matter expertise on SQL, Python, and cloud analytics environments. The Lead trains and mentors Data Stewards on key platforms such as Snowflake, Databricks, and Azure Synapse Analytics (ASA), helping elevate data literacy and operational consistency across the organization.

This position requires strong strategic thinking, the ability to collaborate across diverse functional groups, and the capability to advise executives on data governance matters of high significance.

• Bachelor's degree
• 8 or more years of technical experience, including hands‑on work with data governance platforms, analytics environments, or data engineering concepts
• 2 or more years of project leadership experience, with demonstrated ability to lead large-scale, highly visible initiatives involving multiple project teams
• Experience with enterprise data governance, including development and execution of data policies, quality standards, stewardship models, and operational governance processes
• Advanced SQL proficiency, including the ability to write, troubleshoot, and optimize complex queries
• Working knowledge of Python for data analysis, transformations, or automation tasks
• Proficiency with enterprise data platforms and cloud ecosystems, such as:
• Snowflake – querying, metadata usage, and access modeling
• Databricks – notebooks, Delta Lake concepts, and data engineering workflows
• Azure analytics tools, including Azure Synapse Analytics (ASA)
• Strong understanding of leading data governance frameworks and principles, including:
• DAMA-DMBOK
• Data lifecycle management
• Metadata management and data cataloging
• Data quality dimensions, rules, and measurement methodologies
• Master and reference data management principles
• Stewardship models and RACI structures
• Lineage tracking, data retention, and policy enforcement
• Demonstrated ability to develop or improve enterprise data governance processes and best practices
• Ability to collaborate across business and IT teams to promote data consistency, accuracy, and quality
• Strong analytical, judgment, and decision‑making capabilities, capable of solving complex problems with minimal oversight
• Ability to train, mentor, and support Data Stewards on enterprise data tools
• Passion for enhancing data‑driven consumer experiences and advancing enterprise data maturity

• Master’s degree
• Experience working in healthcare or other regulated industries
• Familiarity with enterprise metadata management platforms (e.g., Collibra, Informatica, Alation)
• Exposure to data engineering practices, automation, or CI/CD pipelines

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