Description

As a Graph Engineer, you will design, build, and optimise scalable RDF-based Knowledge Graphs to support advanced semantic querying and analytics. You’ll focus on ontology modelling, data ingestion, and Graph DevOps, working closely with data and business teams to unify complex data domains into a high-quality semantic architecture.

Key Responsibilities

·        Build and maintain RDF Knowledge Graphs.

·        Load and combine data from different sources.

·         Create and manage ontologies and semantic models.

·         Ensure data quality and consistency.

·        Write and optimise SPARQL queries.

·        Support automation, CI/CD, and version control for graph solutions.

·        Improve graph performance and scalability.

·        Work closely with data and business teams.

·        Share knowledge and support others using Knowledge Graphs.

Required Skills & Experience

• Strong expertise in RDF, SPARQL, and OWL semantic standards.
• 3–5+ years’ experience designing, building, and optimising RDF-based Knowledge Graphs or semantic data solutions.
• Hands-on experience with graph databases and triple stores (e.g. Stardog, Neo4j, Apache Jena, Amazon Neptune).
• Proven capability building data ingestion and integration pipelines across multiple data sources.
• Experience with Python and SQL, and working knowledge of CI/CD tooling (e.g. Jenkins, Terraform, Git).
• Familiarity with cloud platforms such as AWS, Azure, or Google Cloud.

Nice to Have

• Experience integrating Knowledge Graphs with AI or machine learning solutions.
• Practical experience using Knowledge Graphs to provide context for LLMs via Graph‑RAG patterns.
• Exposure to time‑series data and data virtualisation technologies

Key Skills

Education

Any Graduate