Sr Manager, Information Architecture Plan & Source

Experteer Overview As Sr Manager, IMSC Information Architecture Plan u**amp; Source, you will shape the information architecture across Innovative Medicine Supply Chain to deliver AI-ready, trusted data assets.You will collaborate with business and technology partners to design scalable, semantically aligned data structures and governance.You will lead end-to-end modelling and ontologies that enable analytics, automation, and AI at scale.This is a chance to influence data strategy in a globally impactful healthcare environment.Compensaciones / Beneficios - Design and implement end-to-end FAIR and AI-ready data assets for functional domains, including master, transactional, operational, and analytical data - Lead conceptual and logical information modelling for assigned domains with clear ownership and reusable structures - Define and apply IA principles, standards, and patterns across metadata, taxonomy, semantic modelling, ontology, business glossary, and data asset design - Establish and maintain domain-level business semantics, including definitions, terms, and mappings - Support development of the AI-ready context layer by connecting metadata, business meaning, relationships, lineage, and knowledge structures - Collaborate with Data Owners and process owners to ensure shared ownership of data meaning and reusable models - Work with Data Governance to embed semantics, metadata standards, and asset lifecycle governance - Partner with Data Operations and Ju**J Technology to translate models into governed data assets - Provide IA oversight for strategic initiatives and architecture reviews to ensure AI readiness and metadata quality - Contribute to the IA operating model, roles, lifecycle processes, and federated working approaches - Support metadata cataloguing, glossary standards, lineage visibility, data contracts, and reusable templates - Lead ontology and knowledge graph implementation for a coherent context layer - Identify and pilot AI-assisted capabilities to accelerate metadata curation and modelling - Create guidance, playbooks, and examples to apply IA standards across domains - Drive IA adoption by simplifying concepts and communicating value to stakeholders - Build awareness of metadata and semantics through education for business and technology teams - Establish and maintain data governance, data quality, data contracts, and lineage practices - Champion automation and AI-assisted workflows to accelerate data modelling and quality processes - Operate with energy, accountability, curiosity, and collaboration to enable capability buildingResponsabilidades - Experience in pharmaceutical, healthcare, life sciences, supply chain, manufacturing, quality, or regulated data environments - Knowledge of FAIR, IDMP, ISO standards, data mesh, domain-driven design, semantic layers, and knowledge graphs - Strong experience in information architecture, data architecture, data modelling, or data management - Deep understanding of FAIR data principles, data product design, metadata management, glossary, taxonomy, and ontology concepts - Experience designing end-to-end data products across multiple data domains - Understanding of how IA enables AI-ready data with semantic consistency and governance - Experience with data catalogues, metadata repositories, glossary, ontology tools, semantic layers, knowledge graphs, lakehouse platforms - Familiarity with Alation, Databricks, Neo4j, TopBraid, SAP S/4HANA, SAP BDC, or similar tools - Ability to translate business needs into reusable information structures and domain models - Experience in federated operating models and cross-functional partnerships - Experience supporting multi-year strategy and technology deployments in information management, data products, analytics, or AI - Strong communication skills to simplify complex topics for senior stakeholders - Proven track record of cross-functional influence and delivering results across global ecosystems - Experience creating standards, templates, and adoption materials for business and technology - Knowledge of data governance, data quality, data contracts, lineage, access controls, and operating models for governed data products - Familiarity with automation and AI-assisted workflows to accelerate data modelling and quality - Energetic, accountable, curious, collaborative with a commitment to continuous learningRequisitos principales -

AI-assisted workflows to accelerate data modelling and quality processes - Operate with energy, accountability, curiosity, and collaboration to enable capability buildingResponsabilidades - Experience in pharmaceutical, healthcare, life sciences, supply chain, manufacturing, quality, or regulated data environments - Knowledge of FAIR, IDMP, ISO standards, data mesh, domain-driven design, semantic layers, and knowledge graphs - Strong experience in information architecture, data architecture, data modelling, or data management - Deep understanding of FAIR data principles, data product design, metadata management, glossary, taxonomy, and ontology concepts - Experience designing end-to-end data products across multiple data domains - Understanding of how IA enables AI-ready data with semantic consistency and governance - Experience with data catalogues, metadata repositories, glossary, ontology tools, semantic layers, knowledge graphs, lakehouse platforms - Familiarity with Alation, Databricks, Neo4j, TopBraid, SAP S/4HANA, SAP BDC, or similar tools - Ability to translate business needs into reusable information structures and domain models - Experience in federated operating models and cross-functional partnerships - Experience supporting multi-year strategy and technology deployments in information management, data products, analytics, or AI - Strong communication skills to simplify complex topics for senior stakeholders - Proven track record of cross-functional influence and delivering results across global ecosystems - Experience creating standards, templates, and adoption materials for business and technology - Knowledge of data governance, data quality, data contracts, lineage, access controls, and operating models for governed data products - Familiarity with automation and AI-assisted workflows to accelerate data modelling and quality - Energetic, accountable, curious, collaborative with a commitment to continuous learningRequisitos principales -