Senior Information Architect – Research & Development

Senior Enterprise Information Architect - R&D Are you ready to architect the semantic foundation that powers AI across R&D and accelerates breakthrough medicines to patients? Step into a senior role where you will define how data becomes connected knowledge across complex scientific, clinical and operational domains. Based in Barcelona, you will be a key member of a global information architecture practice, leading the design and governance of ontologies, taxonomies, canonical models and metadata standards that make R&D knowledge discoverable, interoperable and AI-ready. You will partner with technology and R&D leaders to connect business capabilities end to end, ensuring our most critical data products and platforms align to strategy and deliver measurable value. Can you lead the shift from fragmented, project-specific models to a reusable enterprise knowledge layer that scales across the portfolio? Your work will set enduring standards, uplift capability across teams and provide the semantic backbone that speeds smarter decisions and, ultimately, better outcomes for patients. Accountabilities: - Semantic Architecture Leadership: Provide architectural thought leadership across R&D, defining ontology, semantic, canonical and metadata assets; shape architectural scope and ways of working for information technology. - Enterprise Modelling and Standards: Drive conceptual, logical, physical and semantic modelling within a defined architecture framework; benchmark against leading practices and maintain coherent blueprints for projects and domains. - Ontology and Taxonomy Stewardship: Define and curate enterprise ontologies, taxonomies, controlled vocabularies and semantic layers that connect knowledge across platforms, data products and knowledge graphs. - Transformation to Reusable Semantics: Lead the transformation from project-specific models to reusable enterprise semantic and context assets with clear standards, governance, tooling, adoption pathways and measurable capability uplift. - FAIR/TRUST and Data Mesh Enablement: Champion FAIR and TRUST data principles; align information architecture outputs to a Data Mesh operating model to improve data product discoverability and interoperability. - R&D Strategy Partnership: Work with business leaders to evolve information and semantic designs that support strategy and scientific priorities; own enterprise IA designs for major capability areas and the shared entities and mappings that connect them. - Program Design Authority and Assurance: Take accountability for enterprise IA in major change programmes; assure project designs for conformance to enterprise ontology and metadata standards through blueprints and design reviews. - AI-ready Data and Analytics Patterns: Select and define architectures for reporting, analytics, data science, digital and AI/ML use cases emphasizing semantic consistency, metadata, lineage, quality and interoperability; enable knowledge-graph use cases. - Governance and Education: Lead architectural governance across fields; develop architectural decisions and progress work through forums and councils; evangelize roadmaps and uplift semantic literacy through education, facilitation and coaching. - Data Integration and Reference Models: Support or lead data integration architecture grounded in canonical and semantic reference models; enforce standard enterprise data element names, characteristics and domains across project lifecycles. - Metrics and Data Governance Enablement: Partner with the Data Office to embed governance in IA builds and provide assurance via standardized metrics, including master data consumption, classification metadata, ontology adoption and semantic coverage. - Work Packages and Demand Management: Specify and manage work packages for in