The Sr. Manager, Data Governance Lead – Domain Specific is responsible for operationalizing the Enterprise Data Council vision across specific domains. They will coordinate activities at the tactical level, interpreting Enterprise Data Council direction and defining operational level impact deliverables and actions to build data foundations in specific domains. The role will also establish and enforce data governance policies and standards to provide high-quality data, easy to reuse and connect to accelerate AI innovative solutions to better serve patients.
Requirements
- Responsible for data governance and data management for a given domain of expertise (Research, Development, Supply Chain, etc.)
- Manage a team of Data Governance Specialists and Data Stewards for a specific domain
- Responsible for operationalizing the Enterprise data governance framework and aligning broader stakeholder community with their data governance needs
- Works with Enterprise MDM and Reference Data to enforce standards and data reusability
- Drives cross functional alignment in his/her domain(s) of expertise to ensure adherence to Data Governance principles
- Provides expert guidance on business process and system design to support data governance and data/information modelling objectives
- Maintain documentation and act as an expert on data definitions, data standards, data flows, legacy data structures / hierarchies, common data models, data harmonization etc. for assigned domains
- Ensure compliance with data privacy, security, and regulatory policies for the assigned domains
- Publish metrics to measure effectiveness and drive adoption of Data Governance policy and standards
- Establish enterprise level standards on the nomenclature, content, and structure of information (structured and unstructured data), metadata, glossaries, and taxonomies
- Jointly with Technology teams, business functions, and enterprise teams (e.g., MDM, Enterprise Data Architecture, Enterprise Data Fabric, etc.) define the specifications shaping the development and implementation of data foundations