Senior Data Governance Analyst

P\S\L Group is a global organisation dedicated to putting information at the service of medicine.  The companies and people of the P\S\L Group aim to improve medical care by serving those who need it, those who provide it, and those who seek to improve it.

To this end, we want our information and education services to contribute to the goals we share with our clinicians, clients and supporters, namely: to accelerate the advancement of medicine and help people enjoy better, longer lives. 

Our key contribution to society is to help clinicians and those who support them provide state-of-the-art medical care. 

Our primary business purpose is to help clients and supporters increase the effectiveness of activities pertaining to scientific communication, medical education and the maintenance of clinician audience intimacy.

The Senior Data Governance Analyst is responsible for advancing enterprise data governance practices and ensuring data assets are managed in a consistent, understandable, and sustainable manner across the organization.

This role establishes and prrleomotes data standards, reviews proposed data changes, governs enterprise reference data, and leads governance initiatives within assigned business domains. Governance initiatives may include stewardship, standards development, reference data management, business definitions, and governance process improvements.

The Senior Data Governance Analyst serves as a governance subject matter expert and is expected to proactively identify risks, challenge approaches that introduce ambiguity or duplication, and drive adoption of governance best practices.

• →Develop, maintain, and promote enterprise data governance standards, policies, and procedures on a recurrent basis, including an issue and exception log, policy library upkeep, stewardship records, and Data governance owned database changes.
• →Identify opportunities to improve data governance visibility, influence, and adherence in P\S\L
• →Identify opportunities to automate data governance practices and lead their delivery with the respective delivering team.
• →Employ Artificial Intelligence tools and techniques into smarter data governance within P\S\L.
• →Track and report on governance health metrics on a regular cadence, including open issues, policy exceptions, reference data change activity, and standards adoption
• →Establish and maintain data naming conventions, business definitions, and governance guidelines.
• →Review proposed data structures, data elements, and data changes to ensure alignment with enterprise standards.
• →Promote reuse of existing data assets and discourage unnecessary duplication of data structures and concepts.
• →Participate in governance stand ups and reviews for new initiatives, projects, and significant data changes.

• Serve as the primary governance lead for assigned business domains, data subject areas, or strategic initiatives.
• Own governance initiatives from planning through implementation.
• Coordinate governance, stewardship, and reference data activities required to support assigned initiatives.
• Partner with business, product, engineering, analytics, architecture, and other stakeholders to achieve initiative objectives.
• Identify opportunities for standardization, simplification, and reuse within assigned domains.

• Establish and document data owners, data maintainers, and data stewards for the key assigned initiatives.
• Partner with business and technical stakeholders to clarify ownership, accountability, and business definitions for enterprise data assets.
• Facilitate discussions related to data definitions, stewardship, governance responsibilities, and cross-functional data concerns.
• Provide governance guidance to business, product, application development, analytics, and data teams.
• Develop a strong understanding of business processes, data flows, and data usage across the organization.

• Govern enterprise reference data assets, including code sets, classifications, hierarchies, controlled value lists, and business taxonomies.
• Define and maintain standards for the creation, modification, approval, and retirement of reference data.
• Identify credible sources of external data, or identify AI-assisted methods to gather or build them within P\S\L’s approved tools.
• Assess, or lead the assessment of the downstream impacts of proposed reference data changes.
• Promote consistency and reuse across enterprise reference data domains.
• Partner with business stakeholders to ensure reference data remains accurate, relevant, complete, and aligned with business requirements.

• Maintain governance documentation, business definitions, metadata, and business glossaries required to support enterprise governance objectives.
• Ensure governed data assets are clearly defined and understandable across business and technical teams.

• 5+ years of experience in Data Governance, Data Management, Business Analysis, Data Stewardship, Data Architecture, Analytics, or related disciplines.
• Experience working with both business and technical stakeholders.
• Strong understanding of data governance principles, stewardship, metadata, and reference data management.
• Understanding of project management practices and terminology.
• Experience facilitating discussions and influencing decisions without direct authority.
• Experience using Jira, Snowflake, and PostgreSQL.
• Strong written and verbal communication skills.

• Experience with business glossaries, metadata management, governance platforms, or data catalog solutions.
• Experience with reference data management or master data management practices.
• Familiarity with data warehousing, analytics, and reporting environments.
• Experience supporting enterprise-scale data initiatives.
• Clinical, healthcare, life sciences, or related domain education and/or experience, with the ability to understand and work with structured medication, medical condition, and related clinical data.
• Working knowledge of recognized references for medications, medical conditions, and related clinical reference data, including common structures, relationships, terminology, and authoritative source data.