We are looking for an experienced Ontology Engineer with strong expertise in ontology engineering and semantic modeling to join our team.

In this role, you will contribute to the design, development, and implementation of ontologies that enhance the interoperability, traceability, and usability of scientific data.

You will collaborate with domain experts, data engineers, architects, and digital teams to translate scientific and business concepts into standardized ontologies and semantic mappings. Your work will enable the creation of context-rich, reusable, and AI-ready data assets across research, development, and manufacturing domains.

Key Responsibilities

• Design, develop, and maintain ontologies, semantic models, and controlled vocabularies for domain and project use cases
• Create and maintain mappings between source data and ontology concepts
• Collaborate with subject matter experts to define terminology, relationships, constraints, and semantic patterns required for accurate representation
• Evaluate external ontologies and assess their quality, relevance, and suitability for integration into existing semantic frameworks
• Contribute to documentation, versioning, governance, and lifecycle management of ontologies and semantic assets
• Support integration of ontologies with knowledge graphs, metadata platforms, and data products
• Ensure semantic consistency, interoperability, and reuse across systems and initiatives

Required Qualifications

• Bachelor’s or Master’s degree in Information Science, Computer Science, Bioinformatics, Cheminformatics, Data Science, or equivalent experience
• Proven experience in ontology engineering, semantic modeling, knowledge representation, or knowledge graphs
• Strong knowledge of W3C semantic web standards including RDFS, OWL, SPARQL, and SHACL
• Experience translating domain requirements into ontologies or semantic representations
• Solid understanding of metadata, controlled vocabularies, identifiers, and semantic interoperability
• Experience working with multiple data sources and collaborating with both technical and domain stakeholders
• Strong analytical, problem-solving, and communication skills

Preferred Qualifications

• Familiarity with biology, chemistry, or pharmaceutical research domains
• Experience with ontology design patterns and understanding of their trade-offs
• Understanding of FAIR data principles (Findable, Accessible, Interoperable, Reusable)
• Domain experience in CMC, scientific data capture, or electronic lab notebook (ELN) environments
• Experience using Atlassian tools (e.g., Jira, Confluence) in Agile environments

Additional Competencies

• Demonstrates a growth mindset and adaptability
• Ability to work effectively within cross-functional and enterprise teams
• Strong attention to detail and commitment to high-quality semantic design

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