Knowledge Graph Engineer

Knowledge Graph EngineerRemobi | Remote | Freelance/Contract | 12-month contract | ASAP start (early September start date ideally) We are Remobi - we help businesses scale and innovate through high-performing, remote nearshore tech teams.We're hiring a Knowledge Graph Engineer to design and build a connected enterprise knowledge layer that unifies structured and unstructured data across business systems. Think graph modeling and ontology development alongside semantic search, contextual retrieval, and AI-driven workflows - not just building schemas in isolation, but working across engineering, architecture, and domain teams to turn business concepts into scalable graph models.What You'll DoDesign scalable knowledge graph schemas using property graph and/or RDF-based modelsDevelop and optimise graph queries using Cypher, SPARQL, or GremlinModel business entities, relationships, hierarchies, and context across domainsBuild ingestion pipelines to transform enterprise data into graph structuresCreate and maintain ontologies, taxonomies, and semantic modelsDefine canonical entity models and semantic mappings across data sourcesSupport entity resolution, metadata enrichment, and relationship extractionDesign and support graph APIs and semantic access layersOptimise query performance, indexing, and traversal efficiencyContribute to metadata, lineage, governance, and access control practicesWhat We're Looking For Must-have:5-7 years of experience in knowledge graph engineering, graph databases, semantic modeling, ontology engineering, or related data architecture rolesStrong hands-on experience with at least one graph platform such as Metaphactory (preferred), Neo4j, AWS Neptune, Stardog, TigerGraph, or GraphDBProficiency in graph query languages such as Cypher, SPARQL, or GremlinExperience designing graph schemas, semantic data models, taxonomies, and ontology-aligned structuresGood understanding of RDF, OWL, semantic web concepts, ontology design, and linked data principlesStrong skills in Python and SQL for data transformation, ingestion, and enrichmentNice-to-have:Experience integrating enterprise data from relational databases, APIs, document repositories, and cloud platformsFamiliarity with data governance, metadata management, lineage, and access control practicesBachelor's/Master's degree in Computer Science, Data Science, Engineering, Information Systems, Mathematics, or related fieldStrong cross-functional communication and collaboration abilitiesWhy This RoleYou'll help build the connective layer behind next-generation AI and semantic applications - shaping how a large enterprise models, links, and reasons over its data. If you want graph engineering work that spans modeling, ontology, and enterprise integration, this is that role.