Job Description
Lead, Data Governance (Master Data Management)
Pearson's data organization is in the middle of a genuine transformation and master data is the foundation it's being built on. We're not here to maintain the status quo. We're rethinking how a global education company defines, trusts, and activates its most critical data assets.
We're looking for a Lead, Data Governance (Master Data Management) to lead this charge: setting the strategy, defining the architecture, and driving the execution of Pearson's enterprise master data capabilities. You'll start with the Customer domain, working through the legacy complexity while simultaneously building the blueprints for how we govern Product, Supplier, and other critical domains in a fundamentally different way.
This is a senior, player-coach role for someone who can hold two things at once: the pragmatism to tackle what's broken today, and the ambition to reinvent how an enterprise thinks about data. You will be shaping Pearson's philosophy around trusted, reusable, governed data and building the systems, products, processes, and culture to make that real.
You'll operate as a thought leader to the business, not just a technical function. That means influencing how Pearson's most senior stakeholders understand and value their data, advocating for data as a strategic product, and helping the organization move from treating data as a byproduct of operations to treating it as a first-class asset.
This role sits within Global Data, a team of builders in the middle of a meaningful modernization. You'll work at the intersection of data engineering, data products, analytics, and business units across a global organization, with the ability to drive real change.
Key Responsibilities
MDM Strategy & Architecture
- Drive MDM vision and roadmap: Define and execute the enterprise master data strategy across the Customer domain and beyond (product, supplier, employee, finance) with a phased roadmap for domain expansion. Challenge the status quo and question inherited ways of working, bring fresh thinking to how best practices are defined, and push the organization toward modern, scalable approaches that reflect where data management should be going.
- Establish best practices: Design and implement MDM architecture standards that serve Pearson's global needs while enabling business units to achieve their goals.
- Data governance: Build and operate a data governance framework including stewardship models, data ownership policies, and dispute resolution processes across BUs.
- Architecture and Design: Define system-of-record vs. system-of-use vs. system-of-truth across Salesforce, Oracle, E-commerce, and other integrated platforms. Drive data model re-design reducing MDM data bloat and ensuring streamlined field use across all BUs and functions.
- Metadata & lineage: Oversee metadata management and data lineage practices to ensure traceability and auditability across the data estate.
- Automation: Identify automation opportunities as it relates to master data CRUD or Data quality.
Customer360 & Self-Service Analytics
- Lead Customer360 data product: Lead the design and build of holistic view of the Pearson customer, a foundational data product that powers self-service analytics across the business.
- Innovative data access: Create and champion new approaches to accessing and consuming master data, enabling business users to answer their own questions without reliance on data teams.
- Single source of truth: Drive the design and adoption of golden record and deduplication processes, match and merge logic that produces a trusted, unified view of each customer across all Pearson systems.
Data Quality & Trusted Data
- Data quality ownership: Define and enforce data quality standards across master data domains, profiling, monitoring, cleansing, and continuous improvement.
- Golden record & deduplication: Lead the design of match and merge processes to identify, resolve, and prevent duplicate records across source systems.
- Data stewardship program: Stand up a data stewardship program that embeds accountability for data quality within business units, not just central IT.
Production Support & Legacy Systems
- Legacy system stabilization: Partner with engineering and operations teams to drive production support for legacy MDM systems while the organization transitions to modern platforms.
- System integration: Ensure master data flows correctly across Oracle, Salesforce, and other enterprise systems, managing integration patterns, data synchronization, and API-based consumption.
- ETL/ELT pipelines: Oversee the design and maintenance of data ingestion pipelines that feed master data from source systems into the MDM platform.
- Master Data Migrations: Support master data migration programs ensuring data quality, standard processes, and approvals are in place before creating or updating data.
- Cross-Functional Partnership & Change Management
- Stakeholder influence: Act as the primary MDM partner to business units, translating complex data capabilities into business value and influencing across a matrixed organization.
- Change management: Drive the cultural and operational change required for MDM transformation, MDM programs succeed or fail based on adoption, not just technology.
- Business & technical fluency: Serve as the bridge between technical data teams and business stakeholders, with a deep understanding of both Pearson's data landscape and the commercial needs of its business units.
- Program Leadership: Serve as the central MDM lead across all major enterprise programs and ensure alignment of requirements and dependencies across the programs.
- Performance Management and Continuous Improvement: Define and track KPIs tied to business outcomes and MDM value realization
Qualifications
Required
- 10–15 years of experience in data management, with significant depth in Master Data Management
- Hands-on experience with MDM platforms such as Informatica
- Deep knowledge of Oracle and Salesforce as source systems and MDM consumers (SFDC – Data360 and Agentforce)
- Proven experience designing match and merge logic, deduplication, and golden record processes
- Large Scale Customer Master / Customer 360 transformations
- Deep understanding of data governance frameworks, data stewardship, and data ownership models
- Experience with ETL/ELT pipelines, API integration patterns, and cloud data platforms
- Track record of driving data quality programs at scale in complex enterprise environments
- Ability to lead cross-functional initiatives and influence senior stakeholders without direct authority
- Experience managing legacy system environments while driving modernization
- Strong communication skills - able to translate technical concepts for business audiences and vice versa
Nice to Have
- Experience with data product thinking and self-service analytics enablement
- Familiarity with Customer360 or similar enterprise customer data initiatives
- Experience with GCP (Looker)
- Experience with metadata management tools and data lineage platforms
- Knowledge of real-time and streaming data architectures
Job Tags
Remote work