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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # IT Master Data Governance Manager - **Company:** Grifols - **Location:** Barcelona, Spain - **Contract:** Permanent contract - **Skills:** Geographic Information Systems, Application Programming Interfaces (APIs), Artificial Intelligence, Business Analytics Applications, Data Analysis, Information Systems, Data Architecture, Data Dictionary, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Transformation, Data Synchronization, Data Warehousing, Interoperability, Metadata, Meta-Data Management, Metadata Standards, Data Streaming, Enterprise Data Management, SAP Integration Solutions, Data Lakes, Information Technology, SAP MDG, Data Management, Data Pipelines, Data Generation - **Published:** August 29, 2026 - **Apply:** https://www.jobleads.com/es/job/e4175d3fef658f7a17755c00d301aca28 ## About the Role To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skills, education, and/or ability required. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions). * Bachelor's degree in Computer Science, Data Science, Information Systems, Engineering or a related field. * Minimum of 5 years of experience in data management, master data management, data governance, data quality, data architecture or enterprise data transformation initiatives. * Experience with MDM concepts and platforms such as Reltio, SAP MDG, Informatica MDM, Semarchy, Profisee or similar solutions, data lakes and data catalog tools. * Knowledge of data governance frameworks, data ownership, stewardship, data quality management, metadata management, cataloging and lineage. Experience with Microsoft Purview. * Understanding of data integration patterns, APIs, ETL/ELT, data pipelines, ERP integration and analytical data platforms. * Advanced English language skills, both spoken and written. * Strong ownership mindset, accountability and ability to drive topics from ambiguity to execution. * Excellent stakeholder management and communication skills, with the ability to influence without direct authority across business and IT teams. Collaboration. * Ability to facilitate workshops, align different perspectives and convert complex data topics into clear decisions and practical actions. * Comfortable operating in a matrixed, global organization and coordinating with teams across functions, geographies and time zones. * Pragmatic, structured and delivery-oriented, with the ability to balance governance discipline with business agility. * Continuous improvement mindset and willingness to build internal capability through knowledge transfer, documentation and enablement. ## Description + Help define, implement and evolve Master Data Management capabilities across key enterprise domains such as customer, supplier, product, material, donor, employee or location data. + Support the definition of golden record rules, matching, merging, survivorship, hierarchy management and data synchronization patterns across systems. + Collaborate with Data Engineering and application teams to integrate master data with ERP, CRM, analytics platforms, data lakes, data warehouses and downstream reporting solutions. + Contribute to the design and operation of MDM workflows for data creation, change, approval, exception handling, de-duplication and lifecycle management. * Data Governance, Quality & Compliance + Support the implementation of data governance policies, standards, ownership, stewardship responsibilities, decision rights and escalation mechanisms. Make data standards available for Advance Analytics consumption: data AI readiness. + Define and monitor data quality rules, KPIs, thresholds and remediation processes to improve accuracy, completeness, consistency, timeliness and trust. + Work with business data owners and stewards to identify root causes of data issues and drive sustainable corrective actions at the source. + Ensure data initiatives consider security, privacy, auditability, regulatory expectations and compliance requirements in a highly regulated environment. + Experience building and maintaining data catalogs for lake house environments, ensuring that high-value analytical variables and datasets are documented, contextualized and reusable for Advanced Analytics, AI use cases and MDM initiatives + Experience defining business ontologies, semantic models and controlled vocabularies to improve data consistency, interoperability, discoverability and AI-readiness across enterprise data domains. + Knowledge of AI governance concepts, data governance for AI, responsible AI principles, privacy-by-design, data risk assessment and emerging regulatory expectations such as the EU AI Act. * Enterprise Data Transformation & Operating Model + Support the execution of the company data transformation roadmap, helping move the organization toward governed, trusted and reusable enterprise data capabilities. + Translate strategic data objectives into actionable initiatives, deliverables, milestones and adoption plans across IT and business domains. + Contribute to the definition and implementation of a hybrid / federated data operating model, balancing central standards with business domain execution. + Drive coordination across Data Office, IT teams, Business stakeholders, external partners and data owners to ensure consistent execution and accountability. * Metadata, Catalog, Lineage & Documentation + Promote the adoption of business glossaries, data dictionaries, metadata standards and cataloging practices to improve discoverability and common understanding of data. + Support the documentation of critical data flows, lineage, transformations, ownership, usage, controls and dependencies across source systems and analytical platforms. + Help establish reusable templates, standards and ways of working for documenting data architecture, MDM domains, data products, data marketplace publishing practices and governance processes. ## Related Videos - [A Data Mesh needs Open Metadata](https://www.wearedevelopers.com/videos/505-a-data-mesh-needs-open-metadata) - [Empowering Retail Through Applied Machine Learning](https://www.wearedevelopers.com/videos/976-empowering-retail-through-applied-machine-learning) - [Blueprints for Success: Steering a Global Data & AI Architecture](https://www.wearedevelopers.com/videos/1577-blueprints-for-success-steering-a-global-data-ai-architecture) - [The Data Mesh as the end of the Datalake as we know it](https://www.wearedevelopers.com/videos/156-the-data-mesh-as-the-end-of-the-datalake-as-we-know-it) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [Crafting Custom Frameworks with Rust: A Deep Dive into Procedural Macros](https://www.wearedevelopers.com/videos/849-crafting-custom-frameworks-with-rust-a-deep-dive-into-procedural-macros) ## Related Articles - [The Most Popular IT Jobs on the Market](https://www.wearedevelopers.com/magazine/376-the-most-popular-it-jobs-on-the-market) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Top-Paying Tech Jobs (with Salaries)](https://www.wearedevelopers.com/magazine/372-top-paying-tech-jobs-with-salaries) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Everything a Developer Needs to Know About MCP with Neo4j](https://www.wearedevelopers.com/magazine/604-everything-a-developer-needs-to-know-about-mcp-with-neo4j)