Knowledge Graph and Semantic Governance Manager

Location: Barcelona - Spain (3 days working from the office and 2 days working from home)

Global Operations Data Office leads the transformation to AI‑ready data that powers Ops 2030. We enable trusted, structured, contextualized data and scalable data products – delivered responsibly. We partner across Pharmaceutical Technology & Development, Manufacturing, Global Engineering, Quality, Sustainability, Global Supply Chain, and Procurement, operating from hubs in the UK, Sweden, US, China, and Global Technology Centres in India and Mexico. Our work directly impacts patients by accelerating digital, data, and AI‑driven operations.

About the Role

We are hiring a Knowledge Graph and Semantic Governance Manager to lead the delivery of the semantic layer strategy for Global Operations. You will:

• Set the semantic strategy and framework for building ontologies and knowledge graphs, guiding standards, platforms, and engineering practices. Understand the way the LLM’s consume and reason over structured knowledge and take this into consideration of the overall sematic strategy and framework.

• Design and deliver ontology‑driven models and embed semantic capabilities into data products and analytics across manufacturing, supply chain, and development. This will require close collaboration with AI/ML engineers and data scientists who builds solutions but also enterprise teams who are shaping and governing the semantic layer.

• You’ll collaborate closely with Operations IT, R&D Semantic Engineering, and the Enterprise Data Office to deliver FAIR, interoperable data that scales AI and automation.

• Govern Global Operations knowledge graphs and ontologies built in alignment with the Global Operations reference model.

• Define the governance Framework for Knowledge graphs and ontologies for Global Operations.

What You’ll Do

• Leadership & Strategy: Design and evolve the semantic strategy and framework for Global Operations; establish and chair/co-chair governance for Global Operations knowledge graphs; define standards, lifecycle, versioning, and stewardship; track and introduce best practices in knowledge representation. Understand how LLM’s consume and reason over structured knowledge.

• Semantic Architecture & Modelling: Set direction for ontology and metadata modelling across Global Operations; oversee design of ontologies, taxonomies, and reference data; ensure alignment with the Operations Reference Data Model and enterprise architecture; guide use of RDF/OWL, SKOS, SHACL, and property graphs (e.g., Neo4j). This requires close collaboration with other teams across AZ enterprise (i.e. other Set area Data Offices, Enterprise Data Office, Enterprise Architecture, AI/ML engineers and data scientists)

• Build Ontologies: Be part of the team that build ontologies enabling the Ops 2030 use cases

• Product and Platform Enablement: Collaborate with It to embed semantic standards into data products, APIs, and integrations; partner with product teams to enable high‑value use cases; influence enterprise selection and use of platforms (GraphDB, Neptune, etc.) and tools (Protégé, VocBench, Metaphactory).

What You’ll Need

• Deep experience leading semantic data/knowledge graph programs in complex, global environments, with delivery of production solutions.

• Proven stakeholder management skills

• Expertise in ontology engineering and semantic web standards (RDF, OWL, SKOS, SHACL, SPARQL) and familiarity with property graph modelling and Cypher.

• Strong background in metadata, taxonomy/thesaurus development, and terminology standardization.

• Proven ability to translate business capabilities into semantic models and data products; effective engagement with both technical and non‑technical stakeholders.

• Solid programming/automation skills and modern engineering practices; Git/GitHub for version control.

• Bachelor’s degree in computer science, Information Systems, Data Engineering, or related; Master’s preferred.

Desirable

• Knowledge of FAIR principles, data governance, and enterprise data architecture.

• Hands‑on experience with Neo4j/Cypher and semantic platforms (GraphDB, Amazon Neptune); tools such as Protégé, VocBench, Metaphactory.

• Exposure to manufacturing and industrial data (ERP, MES, IoT; Cognite Data Fusion).

• Experience applying graphs in AI/ML (embeddings, reasoning, LLM integration).

Why Join Us?

Join a team with the mandate and investment to scale data and AI across Global Operations. Your work will directly impact patients by accelerating how we develop and deliver life‑changing medicines. You’ll lead cross‑company change—building partnerships and ecosystems, modernizing ways of working, and delivering semantic foundations that drive speed, interoperability, and smarter decisions.

When we put unexpected teams in the same room, we unleash bold thinking with the power to inspire life-changing medicines. In-person working gives us the platform we need to connect, work at pace and challenge perceptions. That's why we work, on average, a minimum of three days per week from the office. But that doesn't mean we're not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world.

Are you ready to make a difference? Apply now and join us in our mission to change lives.

Date Posted

25-mar-2026

Closing Date

29-mar-2026

AstraZeneca embraces diversity and equality of opportunity.  We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills.  We believe that the more inclusive we are, the better our work will be.  We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics.  We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.