Specialist Data Management

Career Category

Engineering

Job Description

ABOUT THE ROLE

The Data Governance Lead will lead the creation, implementation and adoption of the Enterprise Data Governance framework across assigned business domains. The role will partner with business, Data Product Owners, Data Stewards, Technology, and enterprise data teams to improve data trust, quality, discoverability, protection, and reuse.

ROLES & RESPONSIBILITIES

• Drive adoption and operationalization of the Enterprise Data Governance framework within assigned domains.
• Partner with Data Product Owners, Data Stewards, business, and Technology teams to establish clear data ownership and accountability.
• Implement governance requirements across data quality, metadata, lineage, access, privacy, security, retention, sharing, and master/reference data.
• Maintain data definitions, business glossary, data standards, classifications, data flows, and other governance documentation.
• Drive cross-functional alignment and adherence to enterprise governance policies and standards.
• Support identification and governance of Critical Data Elements and other high-value data assets.
• Partner with business and technology teams to define and monitor data quality requirements and remediation.
• Support metadata management and data catalog adoption to improve data discovery and reuse.
• Ensure applicable privacy, security, regulatory, and compliance requirements are embedded into governance processes.
• Identify governance gaps and risks and drive appropriate remediation actions.
• Support Data Governance councils, stewardship forums, governance metrics, and maturity reporting.
• Promote data literacy, accountability, and adoption of governance practices across business domains.

MUST-HAVE FUNCTIONAL SKILLS

• Strong experience in Data Governance and Data Management, including metadata, data quality, MDM, stewardship, lineage, privacy, and data standards.
• Experience operationalizing enterprise or domain-level Data Governance frameworks, policies, and processes.
• Experience with business glossaries, data dictionaries, ownership, stewardship, and governance metadata.
• Experience with Data Governance/catalog tools such as Collibra, Alation, Informatica, or similar.
• Good understanding of data quality rules, monitoring, issue management, and remediation.
• Ability to understand business processes, data flows, data models, and upstream/downstream data dependencies.
• Strong stakeholder management and ability to influence across business and technology teams.
• Working knowledge of SQL or similar data analysis techniques.

GOOD-TO-HAVE FUNCTIONAL SKILLS

• Experience with Data Product and Data Product Lifecycle Governance, including ownership, metadata, quality, access, certification, reuse, and retirement.
• Understanding and practical application of FAIR principles — Findable, Accessible, Interoperable, and Reusable — or similar data management frameworks.
• Strong functional/domain knowledge in areas such as Research, Clinical Development, Regulatory, Supply Chain, Commercial, or other enterprise functions.
• Experience working with Data Governance councils, stewardship forums, or governance operating models.
• Knowledge of governance maturity metrics, scorecards, and KPIs.
• Familiarity with cloud data platforms, semantic models, ontologies, or knowledge graphs.
• Experience in pharmaceutical, biotechnology, healthcare, or another regulated industry.
• Familiarity with Agile/Scrum delivery methodologies.

SOFT SKILLS

• Strong analytical and problem-solving skills.
• Excellent written and verbal communication.
• Strong stakeholder management and influencing skills.
• Ability to work effectively across global and cross-functional teams.
• Ability to manage multiple priorities and drive change in a matrixed environment.

BASIC QUALIFICATIONS

• Bachelor's or Master's degree in Computer Science, Information Systems, Data Science, Engineering, Business, Life Sciences, or related field.
• 8–13 years of relevant experience, with significant experience in Data Governance, Data Management, Data Quality, Metadata Management, MDM, or related disciplines.

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