Senior Ontology Engineer

Andersen is a global software development company with over 18 years of experience supporting businesses worldwide in their digital transformation. Headquartered in Poland, they operate development centers across multiple countries, delivering end-to-end IT services including custom software development, API integration, system architecture, and legacy modernization. Their expertise encompasses AI, Machine Learning, Data Science, Big Data, and Visual Technologies, creating intelligent, scalable digital products. Andersen has a portfolio of long-term partnerships with major clients across industries including Healthcare, FinTech, Logistics, Automotive, Manufacturing, E-commerce, and Multimedia & Entertainment, employing 3,700+ experts globally.

• Bachelor's degree in Computer Science, Information Science, Computational Linguistics, Mathematics, or related fields.
• 5+ years of hands-on experience in ontology engineering, semantic data modeling, or knowledge graph development with production ontologies at scale.
• Deep expertise in W3C semantic web standards: RDF, RDFS, OWL, SPARQL 1.1, and SHACL.
• Experience building and validating graph schemas in production triplestores like Amazon Neptune, Stardog, GraphDB, or Jena.
• Strong Python skills, including production-quality, well-tested code; experience building data pipelines and graph processing workflows.
• Understanding of description logics, ontology design patterns, and trade-offs between OWL expressivity and triplestore scalability.
• Experience with entity resolution, record linkage, or deduplication at scale.
• Strong communication skills to defend ontological modeling decisions and explain trade-offs to non-specialists.

Nice to have:

• Experience working with Agile methodologies.

• 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.