Knowledge Graph and Semantic Data Engineer

About the role:
We're looking for an experienced engineer to design and build enterprise knowledge graphs and semantic data layers. You'll work at the intersection of data architecture, AI, and business domains — formalizing business knowledge into machine-readable models.

Responsibilities:

• Design, develop, and implement enterprise-grade knowledge graphs
• Build semantic layers that establish shared business understanding across enterprise systems
• Model business entities, relationships, taxonomies, ontologies, and controlled vocabularies
• Create semantic data products for AI applications, analytics platforms, and business users
• Design enterprise metadata models and integrate them with data catalogues
• Connect structured and unstructured enterprise data within a unified semantic model
• Maintain governance, lineage, metadata quality, and semantic consistency

Requirements:

• Hands-on experience designing and implementing knowledge graphs
• Semantic technologies: RDF, OWL, SKOS, SPARQL
• Graph databases: Neo4j, Amazon Neptune, Stardog, GraphDB, or equivalent
• Enterprise metadata management & data catalogue platforms
• Experience developing ontologies, taxonomies, and controlled vocabularies
• Strong enterprise data architecture and data modelling knowledge
• Advanced SQL and multi-system data integration
• Cloud platforms: Azure, AWS, or GCP

Nice to have:

• Semantic or enterprise search solutions
• Master Data Management (MDM)
• Data Mesh / Data Product concepts
• Enterprise data governance frameworks
• AI agents, GenAI, or RAG architectures