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