Ontology Architect
Dun & Bradstreet
Job Level
Mid-LevelSenior
About the role
- Designing, validating, implementing, and managing the knowledge graph and ontology structure within Dun & Bradstreet
- Applying the ontology hands-on in the development of new data supply chains
- Guiding the development of our future data architecture—balancing long-term vision with short-term wins
- Collaborating in cross-functional teams and project-based environments to ensure effective and sustainable ontology development
- Ensuring our data architecture meets compliance requirements for both Dun & Bradstreet and local markets
- Integrating mature data governance processes in line with our overall data governance strategy
- Communicating and educating internal stakeholders about the purpose and value of the ontology, while actively gathering and incorporating feedback
- Designing the future ontology architecture and guiding its gradual implementation across Dun & Bradstreet Europe
- Supporting implementation of automated data management processes and privacy/compliance by design
Requirements
- Degree in Library Science, Information Systems, Linguistics, other relevant fields, or equivalent work experience
- 3+ years of experience in a similar role working with ontology and/or taxonomy, large quantities of data/information (e.g., data scientist, information architect, or data analyst)
- Experience and expertise in modelling of data/information
- Ability to dive into very different topics and abstract from the details to identify patterns
- Proven track record of strong communication and interpersonal skills; ability to quickly understand complex processes and communicate them in simple language
- Proficient English language skills
- Comfortable working independently and in virtual/cross-functional teams
- Preferred: Experience with requirements engineering of data
- Preferred: Experience of Data Governance
- Preferred: Familiarity with Semantic Web technologies (RDF/s, OWL, SKOS), query languages (SPARQL), and validation/reasoning standards (SHACL, SPIN)
- Preferred: Knowledge of open-source and/or commercial ontology engineering editors (e.g., Protege)
- Preferred: Master’s degree in Library Science, Information Systems, Linguistics or other relevant fields
