Senior Ontology Engineer

Description

The project focuses on building a large-scale Knowledge Graph and Identity platform that models relationships between audiences, content, brands, devices, and behavioral data. It combines graph technologies, big data processing, and AI-powered enrichment to support identity resolution, audience intelligence, measurement, and advanced analytics.

Responsibilities

• Own the end-to-end design, development, and versioning of core RDF/RDFS/OWL ontologies and SHACL validation frameworks.
• Define ontology standards, derived-attribute schemas, aggregation and scoring logic, and governance practices aligned with W3C and relevant industry standards.
• Lead ontology design reviews and translate business requirements into scalable knowledge graphs and semantic data models.
• Co-design derivation and transformation pipelines with Data Engineering using Databricks/Spark, including schemas and validation checkpoints.
• Build scalable, production-grade knowledge graph pipelines using Python and SPARQL, including entity resolution, record linkage, and data enrichment.
• Define graph-versus-data-lake strategies to balance query performance, storage, scalability, and refresh costs.
• Apply embeddings and LLM-based approaches to ontology mapping, entity disambiguation, semantic similarity, and GraphRAG use cases.
• Collaborate with Data Engineering, Data Science, Platform, and Product teams to ensure production-ready graph solutions.
• Mentor Ontology Engineers and junior specialists and lead technical workshops on ontologies, knowledge graphs, and semantic technologies.

Must-haves

• Bachelor’s degree in Computer Science, Information Science, Computational Linguistics, Mathematics, or a related field.
• 5+ years of hands-on experience in ontology engineering, semantic data modeling, or knowledge graph development, 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, such as Amazon Neptune, Stardog, GraphDB, Jena, or equivalent.
• Strong Python skills, including production-quality, well-tested code, and the ability to build data pipelines and graph-processing workflows.
• First-principles understanding of description logics, ontology design patterns, and trade-offs between OWL expressivity and triplestore scalability.
• Hands-on experience with large-scale entity resolution, record linkage, or deduplication across messy, multi-source data.
• Strong communication skills and the ability to defend modeling decisions in design reviews and explain trade-offs to non-specialist stakeholders.
• English level: Intermediate+.

Nice-to-haves

• Master’s degree or PhD in Computer Science, Information Science, Computational Linguistics, Mathematics, or a related field.
• Experience with Amazon Neptune or Stardog, including data virtualization over data lake sources using Neptune Orion or Stardog Virtual Graphs.
• Experience designing aggregation and derivation logic that transforms raw behavioral event data into durable, graph-resident derived attributes.
• Domain knowledge in media, entertainment, or ad tech, including TV viewership, digital audience modeling, device graphs, identity resolution, or ad exposure data.
• Familiarity with EIDR, Schema.org VideoObject, DDEX, or equivalent content and identity schemas.
• Experience with embedding models, vector databases such as Milvus, Pinecone, or Weaviate, and GraphRAG architectures using LangChain or LlamaIndex.
• Familiarity with GNN-based approaches to knowledge graph reasoning or entity resolution.
• Working knowledge of PySpark and Databricks for large-scale transformation pipelines.

Benefits

• Opportunity to change projects and develop expertise in different business domains.
• Professional, financial, and career growth, with mentoring and onboarding support.
• Opportunity to earn an additional annual bonus of up to 1,000 EUR per month depending on expertise and participation in company activities.
• Access to a corporate training portal.
• Certification compensation for certifications such as AWS and PMP.
• Referral program.
• Private health insurance and sports compensation, depending on employment type.