Senior Data Architect - Semantics & Know

 

At Bayer we’re visionaries, driven to solve the world’s toughest challenges and striving for a world where ,Health for all, Hunger for none’ is no longer a dream, but a real possibility. We’re doing it with energy, curiosity and sheer dedication, always learning from unique perspectives of those around us, expanding our thinking, growing our capabilities and redefining ‘impossible’. There are so many reasons to join us. If you’re hungry to build a varied and meaningful career in a community of brilliant and diverse minds to make a real difference, there’s only one choice.

 

Senior Data Architect - Semantics & Know 

 

Purpose 

 

As a Senior Data Architect for Semantics & Knowledge Engineering, you are part of Bayer's Data & AI Team that co-creates domain-specific data products that provide timely, high-quality data to scientists, analysts, and AI agents, with a strong emphasis on semantics as the foundation for AI-readiness. 

You elicit, structure, and formalize knowledge from domain experts and diverse sources to build ontologies, semantic layers, and knowledge graphs that form the connective tissue of an integrated pharmaceutical data landscape. Your work directly enables secondary data use, self-service analytics, and agentic AI capabilities. This role operates at the intersection of knowledge engineering and data architecture, combining formal knowledge representation with pragmatic, engineering-driven delivery in a cloud-based environment. 

 

Your Tasks & Responsibilities:

 

 Data Modelling 

• Design and implement conceptual, logical, and physical data models and semantic layers to enable consistent use. 

• Design, build and maintain ontologies, taxonomies, and knowledge graphs using both triple stores and labeled-property graph technologies, including virtual knowledge graph approaches where appropriate.  

• Collaborate with domain experts, data scientists, data engineers, and product teams to elicit tacit knowledge, validate knowledge representations, and ensure accuracy and completeness. 

Data Integration 

• Deliver well-designed solutions to integrate, unify and synchronize data across systems. 

• Design data-oriented APIs and integration patterns that decouple data from source systems and make knowledge structures interoperable and consumable by humans, systems, and AI agents. 

Software Engineering 

• Monitoring of emerging technologies and frameworks in knowledge engineering, data integration, and semantic AI. 

• Active participation in code reviews and collaborative engineering practices to ensure quality of deliverables. 

Data Strategy 

• Drive cross-team alignment on data and knowledge architecture decisions spanning both long-term ambition and near-term execution. 

• Active alignment of data initiatives with business, digital, and IT strategies to ensure the respective needs are addressed most efficiently and effectively. 

Data Governance & Standards Leadership 

• Embrace FAIR Data Principles and Linked Data standards to promote a data culture that shifts from siloed thinking to networked, democratized data use. 

Data Security & Compliance            

• Design and implement appropriate measure to protect data fromunauthorized access, corruption, or theft, ultimately ensuring confidentiality, integrity, and availability of data to maintain trust in data and prevent legal, operational, regulatory and financial risks.

 

Qualifications & Competencies (education, skills, experience):

 

Required: 

 

• Bachelor’s Degree in computer science, information science, knowledge engineering, computational linguistics, or a related field, or equivalent practical experience 

• Proficiency in designing and implementing data models (conceptual, logical, and physical) 

• Advanced knowledge of ontologies and taxonomies with proficiency in Semantic Web technologies, standards, and tools (e.f. RDF, OWL, SHACL, SPARQL, TopBraid EDG) 

• Proficiency with graph databases covering both triple stores and labeled-property graph systems, including virtual knowledge graph technologies such as Ontop or Stardog 

• Extensive experience API design patterns such a