Lead, Master Data Management and Governance

About the Role:
Grade Level (for internal use):
12
The Role:
Lead, Master Data Management and Governance
The Team:
S&P Global advances essential intelligence through world-leading data, benchmarks and insights. As Lead of Master Data Management and Governance within our Internal Data Fabric (Enterprise360) team, you'll define how the operational data that runs our business is mastered, governed and certified — so that people and AI agents across the business are working from a foundation of trusted data.
In this role you will define, operate and continuously improve how our most important enterprise entities, reference data and business definitions are mastered, described, certified and trusted across the organization. You will own the governance model that sits on top of our Databricks, Microsoft Fabric and Power BI estate, while leveraging a sophisticated ecosystem of supporting applications – an enterprise data catalog (data.world, with Unity Catalog and Fabric IQ as sub-catalogs), a knowledge-graph backed ontology (RDF) for semantic and reference data standardization, and automated data quality monitoring (Anomalo). You will lead the stewardship community that certifies data within the data catalog, and connect certification to our automated metadata generation path so that definitions are written once, reviewed by the data owner, and reused everywhere.
The Impact:
The Lead, Master Data Management and Governance will be instrumental in making our data trustworthy, discoverable and ready for AI. By establishing a single, certified meaning for key entities and metrics this role will reduce conflicting definitions, remove duplicated effort across teams, and ensure analytics, Power BI reporting and agentic AI solutions are built only on data that has been defined, owned and quality-checked. The work has downstream impact on our customers and colleagues alike, enabling faster, more confident decisions and a stronger foundation for enterprise-grade AI.
What’s in it for you:
Own a high-impact, enterprise-wide capability: Take accountability for master data and certification across the Internal Data Fabric, a role with visibility across technology leadership, data owners and business stakeholders.
Work at the intersection of governance and AI: Gain hands-on experience with Databricks, Microsoft Fabric, Power BI, knowledge graphs and automated metadata generation in a live enterprise environment.
Shape how meaning is managed: Directly influence how business definitions, ontology and certification are designed so that people and AI agents can find, understand and trust our data.
Strong learning and growth opportunities: Collaborate closely with Enterprise Data Architecture, Data Governance and engineering colleagues, and grow as a leader of both a stewardship community and a specialist team.
Responsibilities:
Define and lead the Internal Data Fabric master data management strategy, roadmap, and execution- including the critical business entities, reference data and hierarchies to be mastered and the systems of record for each.
Design and operate the data governance and stewardship model: roles, responsibilities, decision rights, escalation paths and operating cadence for data owners and data stewards.
Drive data certification through the enterprise data catalog (data.world), working with stewards and owners to ensure data, metrics and reports are defined, described and signed off as expected before they are certified for consumption.
Integrate certification with the metadata generation path, so that generated descriptions, classifications and ownership are proposed automatically, reviewed and approved by stewards, and published back to the data catalog with a clear audit trail.
Partner with internal teams on the enterprise data catalog implementation (data.world) and lead its integration with the Unity Catalog and Fabric IQ sub-catalogs, keeping technical, business and quality metadata consistent and ensuring metadata flows in a single, well-defined direction.
Govern the enterprise ontology (RDF graph): set modeling standards, manage change and release of concepts and relationships, and ensure business definitions are authored once and referenced everywhere, rather than redefined locally.
Define and maintain entity resolution and golden-record rules for mastered entities, working with data engineers to implement them in the gold tier of the Databricks medallion architecture.
Define data quality rules, thresholds and certification criteria, and use data quality tooling (Anomalo) and/or mechanisms to monitor coverage, detect anomalies and surface quality results and certification state in the data catalog.
Establish and enforce data standards for naming, descriptions, data types, reference codes and classification, aligning internal dictionaries with Enterprise Data Architecture standards and the EDA Style Guide.
Manage the decertification and recertification path, including how owners and consumers are notified and triggering appropriate workflows when certified data degrades.
Define and report governance KPIs and Power BI dashboards covering certification coverage, steward activity, metadata completeness, data quality trends and issue resolution.
Partner with Enterprise Data Architecture, Knowledge Engineering, Data Engineering, Security and business data owners to embed governance into onboarding, data product design and delivery.
Serve as the technical lead and mentor for the team, establishing best practices and operating principles; ultimately accountable for the quality, integrity and trustworthiness of mastered and certified data.
Lead and develop a team of data governance and master data specialists, and coach the wider steward community.
What We’re Looking For:
Key qualifications:
Experience: 8+ years in data management, master data management or data governance, including experience leading or coordinating a team or cross-functional governance effort.
Education: Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field - or equivalent professional experience.
MDM Expertise: Solid understanding of master and reference data concepts such as entity resolution, golden records, hierarchies and data model governance.
Data Governance & Stewardship: Experience running or supporting stewardship and certification processes, including ownership models, policies, data classification and metadata standards.
Data Catalog: Hands-on experience with an enterprise data catalog (data.world / ServiceNow preferred; Collibra, Alation, Purview or similar considered), including business glossary and metadata management.
Data Quality: Experience defining data quality rules and using quality or observability tooling to monitor and report on them.
Platform Knowledge: Working knowledge of Databricks or Microsoft Fabric, familiarity with Power BI, and SQL skills for profiling and analysis.
Preferred qualifications:
Experience with data.world, including certification workflows, and with Anomalo for data quality monitoring.
Working knowledge of Unity Catalog and Fabric IQ and how they feed an enterprise catalog.
Knowledge of RDF, OWL, SPARQL and ontology design, and of how a knowledge graph represents business meaning and relationships.
Understanding of automated or AI-assisted metadata generation and of human-in-the-loop review that agents and downstream AI solutions can rely on.
Familiarity with DAMA-DMBOK and published reference code standards (such as ISO 3166 and ISO 4217), and with enterprise data standards review processes.
Experience with the medallion architecture and Python for profiling and automation.
Experience leading a team of governance or master data specialists.
Soft Skills:
Leadership & People Management: Ability to lead, mentor and inspire a technical team and to influence a community of stewards who do not report to you.
Stakeholder Management: Skilled at aligning data owners, architecture and engineering teams on definitions, timelines, scope and trade-offs.
Communication: Able to translate governance and ontology concepts into clear, actionable guidance for a wide, non-technical audience.
Problem Solving: Pragmatic, data-driven approach to resolving conflicting definitions, ownership gaps and data quality challenges.
What’s In It For You?
Our Mission:
Advancing Essential Intelligence.
Our People:
We're more than 35,000 strong worldwide—so we're able to understand nuances while having a broad perspective. Our team is driven by curiosity and a shared belief that Essential Intelligence can help build a more prosperous future for us all.From finding new ways to measure sustainability to analyzing energy transition across the supply chain to building workflow solutions that make it easy to tap into insight and apply it. We are changing the way people see things and empowering them to make an impact on the world we live in. We’re committed to a more equitable future and to helping our customers find new, sustainable ways of doing business. Join us and help create the critical insights that truly make a difference.

Skills
Python, SQL, Databricks, Power BI, Onboarding

Experience
8+ yrs