Master Data Architect

Job Title: Master Data Architect
Organisation Overview:

Our Client operates at the forefront of data management and digital transformation, delivering enterprise-wide master and reference data solutions across multiple industries. Renowned for fostering innovative cultures that embrace new technologies, our Client offers a dynamic environment characterised by collaboration, continuous learning, and a commitment to excellence. Joining their team means being part of a forward-thinking organisation that values strategic thinking, technical expertise, and impactful results.
Role Summary:

This is a high-profile, strategic role created to lead the architectural design of master and reference data solutions that underpin critical AI and analytics workflows. As organisations increasingly rely on trusted data for decision-making and automation, this position plays a vital part in shaping scalable, tool-agnostic data architectures. The opportunity involves spearheading multi-domain initiatives that ensure data consistency, quality, and governance, thereby enabling smarter business outcomes.
Responsibilities:

• Architect end-to-end master data management (MDM) solutions, covering hub patterns, survivorship, hierarchy management, and golden record creation.
• Design enterprise reference data frameworks, aligning standards, taxonomies, and conformed dimensions with organisational semantics.
• Lead multi-domain data architecture efforts across key areas such as customer, product, supplier, and other critical master data domains.
• Develop data models and strategies that support AI/ML workflows, including feature store readiness and data lineage tracking.
• Connect master and reference data frameworks to semantic layers, ontologies, and business glossaries, ensuring semantic consistency.
• Evaluate and recommend platform solutions based on client needs, leading implementation and configuration on preferred platforms.
• Define integration patterns for distributing master and reference data via APIs, events, batch processes, and real-time streams.
• Establish matching, deduplication, and survivorship strategies for entity resolution across systems.
• Collaborate with Data Governance and Metadata teams to align architecture with broader governance frameworks.
• Provide advisory support to senior stakeholders, translating complex architectural trade-offs into business strategies.
• Create reusable architecture artefacts, design patterns, and operational procedures to facilitate scalable implementation.

Essential Skills & Experience:

• Over 10 years’ experience in master data and reference data architecture, including leading multiple full-cycle MDM or RDM projects.
• Extensive hands-on experience across at least three core master data domains, with a strong grasp of data modelling, hierarchy management, and survivorship.
• Proven ability to operationalise reference standards and integrate them with enterprise systems.
• Practical experience implementing on major MDM platforms and transferring architecture patterns across different tools.
• Deep understanding of integration architectures involving APIs, event-driven patterns, ETL/ELT, and change data capture.
• Strong stakeholder engagement skills, able to communicate complex concepts clearly to technical and non-technical audiences.
• Relevant degree or professional qualifications in Computer Science, Information Management, or related fields.

Desirable Skills & Experience:

• Experience with multiple MDM platforms such as Informatica, Reltio, Semarchy, Profisee, or IBM MDM.
• Familiarity with semantic layer concepts, ontologies, taxonomies, and knowledge graphs.
• Cloud-native architecture experience on Azure, AWS, or GCP.
• Industry background in regulated environments such as life sciences, financial services, or healthcare.
• Knowledge of industry standards like LEI, ISIN, SNOMED, LOINC, or GS1.
• Certifications such as CDMP, IQCP, or platform-specific MDM certifications.
• Experience supporting AI/ML initiatives with master data pathways and feature store integration.

What Success Looks Like:

By the conclusion of engagement, the Architect will have delivered a comprehensive, integrated data architecture aligned with best practices, enabling scalable AI and analytics initiatives. This includes finalised current-state assessments, a documented target architecture, and operationalised solutions within key domains. The role will have established governance controls, reusable patterns, and clear stakeholder communication, positioning your organisation to trust and leverage their master data assets effectively.

Interested candidates are encouraged to submit their CVs outlining relevant experience for immediate consideration. This is an excellent opportunity to influence strategic data initiatives and work with diverse teams on impactful projects.