Senior Data Governance Analyst, MDM/RDM

Overview

The Senior Data Governance Analyst, MDM/RDM contributes to the consistent implementation of Parexel’s data governance frameworks and contributes to the development of high-quality, well-managed master and reference data (MDM and RDM). This role focuses on the day-to-day operational management of MDM/RDM processes, issue resolution, collaboration with global data stewards across domains such as Investigator, Site, and Study, and the alignment of master and reference data across Parexel. Operating within the Data Governance Enablement team, this role collaborates closely with data governance leadership, data domain owners, data and technology (D & T), and business stakeholders to enable the accuracy, consistency, and usability of master and reference data.

Key Accountabilities

Data Management:

• Contributes to the implementation of the established MDM/RDM roadmap in partnership with data governance leadership, including participation in user acceptance testing (UAT) to validate new or updated master and reference data processes, data models, and system functionality.
• Perform day-to-day activities for managing master data and reference data across domains.
• Translate business needs into clear, actionable requirements for D & T development teams.
• Evaluate data dependencies, downstream impacts, and alignment with architectural and governance standards. Support MDM/RDM curation and lineage.
• Ensure that master and reference data processes align with policies, business rules, and stewardship expectations.
• Maintain alignment across MDM/RDM assets, data catalogs, and repositories.
  
  

• Monitor, investigate, and triage issues related to master and reference data quality, escalating when necessary.
• Collaborate with business and technical teams to solve data issues and identify process improvements.
• Support enhancements to MDM/RDM workflows, process updates, documentation, and training materials.
• Provide guidance on best practices for maintenance and change control activities related to MDM/RDM data, processes and governance expectations.
  
  

• Build strong working relationships with global data stewards, business partners, D & T teams, and data governance peers.
• Support cross-functional initiatives requiring master or reference data expertise.
• Maintain a log of MDM/RDM data owners for issue resolution, decision-making, escalation, and communication pathways.
• Contribute subject-matter expertise related to MDM/RDM practices.
  
  

• Assist with planning and evaluating future MDM/RDM tools, capabilities, and enhancements.
• Contribute to the reporting of MDM/RDM metrics, KPIs, and adoption indicators.
• Ensure alignment with data privacy, data protection, and regulatory considerations relevant to clinical research datasets.
  
  

• Strong knowledge of Master Data Management and Reference Data Management principles and processes.
• Understanding of data governance frameworks, metadata practices, and data lifecycle management.
• Excellent problem-solving, analytical, and organizational skills.
• Clear written and verbal communication skills; ability to translate complex data concepts into business-friendly language.
• Ability to work effectively in a global, matrixed environment and collaborate across cultures and time zones. Strong team-first mindset.
• Demonstrated professionalism, follow-through, and ability to work independently.
• Balanced approach to short-term needs and long-term governance expectations.
• Ability to manage multiple tasks simultaneously and adapt to changing priorities.
  
  

• Experience implementing or supporting MDM and RDM capabilities in an enterprise environment.
• Familiarity with MDM platforms, reference data tools, and enterprise information management practices. Familiarity with Reltio or similar enterprise platform is helpful.
• Experience contributing to data governance or data analytics initiatives.
• Experience working with global teams in a matrixed organization.
• Understanding of data privacy, data protection, and data quality principles.
• Experience in life sciences, pharmaceutical, or CRO environments beneficial.
  
  

• Degree in information science, data analytics, information systems, life sciences, or related field preferred.