Senior Information Architect – Research & Development
AstraZeneca · Barcelona, Spain · Global
Health Informatics
–
physician
Demand82
Career growth78
Healthcare fit58
Remote potential55
5-year outlook
Senior pharma information architecture roles generally sit in the enterprise-technology salary band, with exact pay depending on location, level, and scope. Demand is likely to grow with AI-ready data, semantics, and governance investment.
Clinical license
Not required
Applicant reach
narrow
Seniority
senior
Employment type
full-time
Date found
2026-10-27
Intelligence details
Flexible work details
- Engagement type
- Permanent
- Hours
- Full-time
- Profession fit
- physician
Eligibility, licensing, and location restrictions can change. Always confirm details on the source posting before applying.
Why this is worth applying to
Worth considering only for clinicians with strong informatics, ontology, metadata, or enterprise data architecture experience. Most clinicians without prior data-platform leadership would find the technical and seniority bar too high.
Who should apply
Clinician-informaticists, physician or pharmacist data leaders, and healthcare graduates with enterprise data architecture, ontology, metadata governance, or data product experience.
CV angle
Reframe real clinical and healthcare data experience into enterprise information architecture language: ontology and taxonomy work, metadata standards, data governance, interoperability, data quality, stakeholder leadership, and measurable adoption. Emphasize any experience with data platforms, knowledge graphs, FAIR principles, or AI-ready data without overstating technical depth.
Skills to highlight
- Semantic architecture
- Ontology and taxonomy design
- Metadata and controlled vocabulary management
- Enterprise data modelling
- Data governance and standards
- FAIR/TRUST and data mesh principles
- Knowledge graph and interoperability concepts
- Architecture leadership and stakeholder influence
Role summary
A senior enterprise information architecture role in AstraZeneca R&D focused on building reusable semantic models, ontologies, metadata standards, and data architectures that support data products, analytics, AI/ML, and knowledge graphs across the research portfolio.
We publish our own intelligence summary, never the full job description. Always confirm details with the employer when you apply.