What's in it for you?
* Cutting-edge role working on enterprise knowledge graphs, semantic tech, and Graph-RAG/LLM use cases.
* Hands‐on engineering focus across ontology design, SPARQL, and production‐grade graph DevOps.
* Flexible 12‐month hybrid contract with 3 days onsite in Melbourne or Sydney.
Role
The Graph Engineer will design, build, and optimise scalable RDF‐based knowledge graphs to enable advanced semantic querying and analytics. This role focuses 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. The position is a 12‐month contract, based in Melbourne or Sydney, with a hybrid work model.
Location – Melbourne (preferred)/ Sydney (secondary)
Contract length – 12 months
Expected 3 days in office per week
Key Responsibilities
* Graph Database Development:
o Design, implement, and optimise RDF graph databases and triple stores to support scalable and performant semantic querying.
o Develop and manage data ingestion pipelines, integrating diverse data sources into the knowledge graph.
* Ontology Modeling and Semantic Mapping:
o Design and implement scalable ontologies and taxonomies (using OWL and RDFS) that accurately represent complex business domains.
o Perform semantic mapping to align disparate data sources into a unified, meaningful graph structure.
o Ensure data consistency and integrity using SHACL or ShEx constraints.
o Build reusable ontology components and templates that accelerate the design‐to‐build phase for new graph projects.
* Graph DevOps & Engineering Tooling:
o Contribute to internal frameworks and tooling that automate ontology generation, semantic mapping, and graph data ingestion workflows.
o Promote best practices for Graph DevOps, including automated validation, testing, and CI/CD pipelines for ontology and graph model deployment.
o Maintain versioning strategies and automated quality checks for RDF models, SHACL rules, and semantic assets.
o Develop efficient SPARQL queries and graph‐based APIs to facilitate data retrieval and analytical workflows.
o Optimise data storage, indexing, and retrieval processes to ensure graph database performance and scalability.
* Semantic Architecture & Best Practices:
o Establish and enforce best practices for graph engineering, including naming conventions, schema design, and versioning strategies.
* Collaboration & Support:
o Actively engage with cross‐functional teams (Data Domain Managers, Knowledge Modelers, Analysts) to support semantic use cases and ensure alignment with business objectives.
o Provide guidance and mentorship on RDF graph technologies to technical teams.
Required Skills & Experience
* Demonstrated expertise with RDF, SPARQL, and OWL semantic standards.
* Minimum 3‐5 years of experience designing, developing, and optimising RDF‐based knowledge graphs and semantic data solutions.
* Proven experience working with graph databases and triple stores (e.g., Stardog, Neo4j, Apache Jena, Amazon Neptune).
* Strong experience building robust data ingestion and integration pipelines from multiple data sources.
* Experience with languages such as Python & SQL and working knowledge of CI/CD frameworks (Jenkins, Terraform and Git).
* Familiarity with cloud services such as AWS, Azure, or Google Cloud for deploying graph database solutions.
Nice to have
* Experience integrating RDF knowledge graphs with machine learning or AI‐driven solutions.
* Experience using Knowledge Graphs to provide context for Large Language Models (LLMs) via Graph‐RAG pattern.
* Time series and Data virtualization experience.
Talented, committed, can‐do individuals have always been the cornerstone of this dynamic organisation. If you have what it takes to thrive in this role and want to know more, please reach out to Isha Khanna at isha.khanna@akkodis.com.
Privacy
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Akkodis is an Equal Opportunity employer, committed to all forms of workforce inclusion. We actively invite and encourage applications by candidates from diverse backgrounds.
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