Senior Ontology Engineer

Andersen is hiring a Senior Ontology Engineer for a project building a large-scale Knowledge Graph and delivering AI-powered data and identity solutions.

The company is a global technology provider delivering data analytics and AI-powered solutions that help organizations better understand customer behavior, optimize marketing performance, and make informed business decisions.

The project is focused on building a large-scale Knowledge Graph and Identity platform that models relationships between audiences, content, brands, devices, and behavioral data.

Responsibilities:

• Owning the end-to-end design, development, and versioning of core RDF/RDFS/OWL ontologies and SHACL validation frameworks.
• Defining ontology standards, derived-attribute schemas, aggregation/scoring logic, and governance practices aligned with W3C and relevant industry standards.
• Leading ontology design reviews and translating business requirements into scalable knowledge graphs and semantic data models.
• Co-designing derivation and transformation pipelines with Data Engineering using Databricks/Spark, including schemas and validation checkpoints.

Must-haves:

• Bachelor's degree in Computer Science, Information Science, Computational Linguistics, Mathematics, or related fields.
• Hands-on experience in ontology engineering, semantic data modeling, or knowledge graph development for 5+ years, with a demonstrable track record of production ontologies at scale.
• Deep expertise in W3C semantic web standards: RDF, RDFS, OWL, SPARQL 1.1, and SHACL.
• Hands-on experience building and validating graph schemas in a production triplestore (Amazon Neptune, Stardog, GraphDB, Jena, or equivalent).
• Strong Python, including production-quality, well-tested code; comfortable building data pipelines and graph processing workflows.
• First-principles understanding of description logics, ontology design patterns, and the practical trade-offs between OWL expressivity and triplestore scalability.
• Hands-on experience with entity resolution, record linkage, or deduplication at scale (mapping messy, multi-source real-world data to clean ontological representations).
• Strong communication skills, ability to defend ontological modeling decisions in design reviews and explain trade-offs to non-specialist stakeholders.
• Level of English – from Intermediate+ and above.