Data & AI Governance Specialist - Master and Reference Data
Listed on 2026-09-10
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IT/Tech
Information & Knowledge Management, Information Security & Data Protection, Data Engineering, AI Business & Operations
About us:
At , data drives our decisions. Technology is at our core. And innovation is everywhere. But our company is more than datasets, lines of code or A/B tests. We’re the thrill of the first night in a new place. The excitement of the next morning. The friends you encounter. The journeys you take. The sights you see. And the memories you make.
Through our products, partners and people, we make it easier for everyone to experience the world
The Data & AI Governance department enables extending the governance theme of policies, standards, processes and technology for governing data and AI to driving excellence in our approach to leveraging secure, trusted, accessible data for data driven decision making through:
An overarching Data & AI Policy to include associated standards
Data & AI Governance including meta and master data management
Data & AI Delivery Governance
Data & AI Quality including both technical and business quality measures
This enables the maturity of Data and AI capabilities across , unlocking data and algorithms as assets for delivering innovative growth opportunities and cost saving operational efficiencies.
RoleDescription:
As a Data & AI Governance Specialist focused on Master and Reference Data, you will help define, implement and continuously improve the standards, guidelines and governance practices that make shared data consistent, understandable, trusted and fit for purpose.
You will work across business and technology domains to ensure common definitions, ownership models, quality expectations, lifecycle rules and change processes for master and reference data. You will translate governance principles into practical guidance that teams can adopt in their data products, platforms and operating processes.
This role combines data governance expertise, standards development, operating model design and stakeholder enablement. Success requires the ability to turn complex data management challenges into clear, actionable and scalable practices.
Key JobResponsibilities and Duties:
Define, review and maintain standards and guidelines for master and reference data, including principles, minimum requirements, roles needed, lifecycle, data quality, controls and implementation guidance.
Establish common approaches for identifying, scoping and prioritising master and reference data domains and data products.
Develop guidance for defining business terms, data elements, authoritative sources, golden records, reference values, critical data elements and other key metadata.
Partner with Data & AI Stewards, Owners, Product Managers, Data & AI Engineers, Architects, Privacy, Security, Risk, Compliance and Legal to embed the standards into delivery and operational processes.
Ensure master and reference data standards are aligned with the Data & AI Governance Framework, Data & AI Policy, classification requirements, privacy obligations, information security principles and applicable regulation.
Contribute to the development of reusable templates, playbooks, patterns, checklists and training materials that help teams apply the standards consistently.
Identify gaps, risks and inconsistencies in master and reference data practices, and coordinate proportionate remediation with accountable stakeholders.
5+ years’ experience in designing and implementing Data Governance and Management in large-scale organisations; AI Governance experience preferred.
Experience designing, implementing or operating Data Governance, Data Management or Master Data Management capabilities in a complex organisation.
Practical experience creating and maintaining data standards, policies, guidelines, playbooks or control frameworks.
Strong understanding of master data and reference data concepts, including domains, entities, attributes, identifiers, hierarchies, taxonomies, code sets and authoritative sources.
Understanding of metadata, data cataloguing, data classification, lineage, critical data elements and data lifecycle management.
Ability to translate business and regulatory requirements into clear, usable standards and implementation guidance.
Experience working across business…
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