Information Architect – R&D; Data & Semantic Architecture (Hybrid Barcelona)
Barcelona, Spain
Work model: Hybrid role with regular on-site presence in Barcelona and close collaboration with global teams.
Key Responsibilities
- Define and maintain enterprise- and domain-level information architecture for R&D; initiatives, aligned with business capabilities and data strategy.
- Develop and govern conceptual, logical, and semantic data models, including ontologies, semantic layers, and Master and Reference Data models.
- Establish and embed data governance standards, principles, and patterns within delivery teams, acting as an architecture assurance authority.
- Support large-scale R&D; transformation programs (clinical planning, supply chain, regulatory submissions, AI initiatives, and data platform modernization).
- Define information architecture roadmaps and transition architectures aligned with enterprise transformation initiatives.
- Facilitate architecture and modeling workshops, translating complex semantic and technical concepts into clear, business-aligned outcomes.
- Collaborate with senior stakeholders across R&D;, IT, Data Office, and product teams, mentoring architects and data modelers as required.
Requirements
Mandatory
- Proven experience as an Information Architect within pharmaceutical or life sciences R&D; environments.
- Strong background in Information Architecture, Data Architecture (conceptual and logical focus), and Data Governance.
- Hands‑on experience with conceptual data modeling, semantic modeling, ontologies, and data integration.
- Solid experience with Master Data Management (MDM) and Reference Data Management (RDM).
- Experience supporting or leading enterprise- or domain-level transformation programs.
- Ability to define architecture principles, standards, and roadmaps.
- Strong stakeholder management, facilitation, and communication skills.
- Advanced level of English (spoken and written).
Nice to have
- Experience working with Enterprise Data Offices (EDO) or formal data governance organizations.
- Knowledge of Data Mesh and Data Product operating models.
- Exposure to AI/ML governance, metadata management, or data catalog initiatives.
- Experience in regulatory, clinical, or late-stage R&D; domains.
- Familiarity with industry standards such as HL7 FHIR, CDISC, or eCTD.
- Certifications such as CDMP, TOGAF, LeanIX, or equivalent.
What We Offer
- Permanent contract with a competitive salary
- Adaptable working model with remote work options
- Personalized career plan and continuous learning (certifications, English training, etc.)
- Participation in stable projects with a strong technical focus
- Flexible working hours and a strong focus on work–life balance
- Benefits package tailored to your needs
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