Ontology Engineer

Andersen is a global technology provider specializing in data analytics and AI solutions. The company builds large-scale Knowledge Graph and Identity platforms connecting audiences, content, brands, devices, and behavioral data to support identity resolution, audience insights, measurement, and advanced analytics.

• Experience with RDF/RDFS/OWL ontology development and graph databases.
• Hands-on SHACL validation, data quality checks, ontology versioning, and schema consistency.
• Strong SPARQL skills and experience with graph traversals.
• Experience building PySpark/Databricks pipelines for high-volume data processing and transformation.
• Strong Python skills: clean, tested, documented, and reusable code.
• Experience with event-to-ontology transformation and graph attribute derivation.
• Familiarity with embeddings, semantic similarity, or vector search for entity matching and ontology alignment.
• Ability to collaborate with data engineering, data science, product, and operations teams.
• Interest in W3C semantic web standards, RDF-native graph databases, and entity resolution.

Nice to have:

• Experience with Amazon Neptune, Stardog, or similar RDF triplestores.
• Knowledge of data virtualization, LLM APIs, or RAG for information extraction and entity disambiguation.
• Background in media, entertainment, or ad tech.
• Experience with identity resolution, probabilistic record linkage, or device graphs.

• Develop and extend RDF/RDFS/OWL ontology schemas, including entity classes, properties, and constraints.
• Build and maintain SHACL validation shapes and support data quality checks.
• Manage ontology versioning, changelogs, and schema consistency.
• Write efficient SPARQL queries and graph traversals.
• Develop PySpark/Databricks pipelines transforming high-volume TV and web activity data into graph attributes.
• Implement derivation logic and validate outputs before graph loading.
• Write clean, tested, reusable Python code.
• Apply embeddings, semantic similarity, and vector search to entity matching and ontology alignment.
• Collaborate with data engineering, data science, product, and operations teams on graph schema and pipeline development.
• Contribute to ontology design reviews, documentation, and team tooling.