Ontology Engineer

Andersen 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 company has over 18 years of experience supporting businesses worldwide in digital transformation, offering end-to-end IT services including custom software development, API integration, system architecture, legacy modernization, and long-term support. Andersen operates development centers across multiple countries including Poland, Germany, the USA, the UK, Lithuania, Hungary, Kazakhstan, Georgia, Azerbaijan, Cyprus, and the UAE.

• Implement and extend RDF/RDFS/OWL ontology schemas in the graph database including entity classes, properties, and constraints.
• Build and maintain SHACL validation shapes for consistency checks.
• Write efficient SPARQL queries and graph traversals to support data science.
• Work with PySpark and Databricks to process and transform high-volume data.
• Apply embedding-based approaches such as semantic similarity and vector search.
• Actively develop expertise in W3C semantic web standards and RDF-native graph databases.

Nice-to-haves:

• Hands-on experience with Amazon Neptune, Stardog, or equivalent RDF-native triplestore; exposure to data virtualization tools.
• Working knowledge of PySpark and Databricks for large-scale event aggregation.
• Familiarity with embedding models, vector search, and semantic similarity applied to entity matching and ontology alignment.
• Experience with LLM APIs or RAG-based approaches for information extraction, entity disambiguation, or schema mapping.

Mile widziane:

• GraphQL
• semantic
• Python
• ontology

Languages:

• English (expert)
• Polish (nice to have)

• Implement and extend RDF/RDFS/OWL ontology schemas in the graph database by adding entity classes and properties.
• Build and maintain SHACL validation shapes for post-load graph consistency checks.
• Contribute to the event-to-ontology transformation and derivation layer by building PySpark/Databricks pipelines aggregating raw TV viewership.
• Implement derivation logic specified by Senior Ontologist and data science team.
• Write clean, well-tested, documented, and reusable production-quality Python code.
• Work with PySpark and Databricks to process and transform high-volume data as part of graph pipeline development.
• Develop expertise in W3C semantic web standards and RDF-native graph databases.