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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Knowledge Graph and Ontology Specialist - **Company:** University of Sheffield - **Location:** Sheffield, UK - **Experience:** Expert - **Salary:** £38,784.0 - £47,289.0 - **Contract:** Temporary contract - **Skills:** Systems Engineering, Continuous Integration, Data Dictionary, Extract Transform Load (ETL), Data Sharing, Software Design Patterns, Graph Database, Information Sciences, Interoperability, Linked Data, Language Modeling, Neo4j, Open Source Technology, Scrum Methodology, Semantic Web, Software Engineering, SPARQL, UML, Git, Knowledge Representation, Information Technology, Software Version Control, Data Pipelines - **Published:** September 8, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=5e8b22b18e01fb3d ## About the Role We offer a fantastic range of benefits including a highly competitive annual leave entitlement (with the ability to purchase more), a generous pensions scheme, flexible working opportunities, a commitment to your development and wellbeing, a wide range of retail discounts, and much more., Are you an experienced knowledge engineer who enjoys solving complex data challenges? We have an exciting opportunity for you to join us as a Knowledge Graph and Ontology Specialist and build the semantic foundations for the future of industrial data., Bachelor's or master's degree in Information Science, Computer Science, Philosophy (with a focus on formal logic/ontology), Systems Engineering, or a related area, coupled with 2-3 years of practical knowledge graph and ontology experience., Working knowledge of foundational upper ontologies (e.g., BORO, HQDM, IES, ISO 15926, BFO, UFO, SUMO, DOLCE) and a demonstrable understanding of 4D (perdurantist / spatiotemporal) vs. 3D (endurantist / spatial) modelling methods in extending domain ontologies., Deep, practical understanding of the distinctions, limitations, and appropriate applications of formal ontologies versus data dictionaries, vocabularies, and taxonomies., Experience with semantic web technologies (RDF(S), OWL, SPARQL, SHACL), standard conceptual modelling languages (e.g., UML or similar) and linked data formats (e.g. Turtle)., Practical experience with ontology authoring tools and workflows (e.g., Sparx Enterprise Architect, Protégé) and familiarity with ontology design patterns and common anti-patterns., Working knowledge and understanding of the differences between graph database technologies (e.g., Neo4j, GraphDB, RDFox) and experience building and managing knowledge graphs that integrate data from multiple sources., Experience translating raw or semi-structured engineering data into structured semantic models, with an understanding of data pipeline or ETL fundamentals., Ability to work in an interdisciplinary environment, interviewing domain experts to translate complex subject matter into formal logic and structured models., Effective communication skills, both written and verbal, including the ability to explain highly abstract conceptual models to non-technical stakeholders., Ability to work effectively as part of an agile team (e.g. scrum, kanban) with a demonstrated capacity to operate independently, alongside excellent time, project management, and collaborative skills., Background or exposure to advanced manufacturing, engineering, or industrial R&D environments. ## Description As a specialist, you will design and develop semantic architectures to make industrial data understandable, interoperable, and queryable. With 2-3 years of experience in knowledge engineering or conceptual modelling, you will establish information pipelines to extract semantic structure from information sources and apply advanced conceptual frameworks (including 3D vs. 4D approaches) to accurately capture complex engineering lifecycles. Please submit a CV and cover letter. In your cover letter, please include: * An explanation and link or attachment to a representative conceptual model or an aspect ontology snippet you have developed. * A brief explanation of a time you had to advocate for a specific modelling approach (e.g., formal ontology over a simple taxonomy)., * Design, build, and maintain formal, machine-readable ontologies (e.g., using UML, RDF(S), SHACL, OWL) to support knowledge representation across multiple high-impact industrially-focused innovation projects. * Apply advanced modelling paradigms, explicitly determining the appropriate use of 3D (endurantist/spatial) versus 4D (perdurantist/spatiotemporal) data modelling approaches to capture the state and lifecycle of engineering and research entities. * Clearly document and differentiate the use of semantic technologies from primitive data dictionaries and taxonomies through to formal ontologies and logic across the project's infrastructure, ensuring the right tool is used for the right semantic requirement. * Work closely with end users, software engineering and data scientists to ensure that all semantic models are FAIR (Findable, Accessible, Interoperable, and Reusable). * Collaborate with the senior technical fellow, industry partners, and domain experts to extract implicit domain knowledge into explicit, rigorous conceptual models. * Design the high-level semantic strategy and lifecycle management for the project's knowledge graphs and data schemas. * Lead the writing of technical documentation, ontology release notes, and contribute to the dissemination of the project's ontological approach. * Provide dissemination and mentorship to research teams on the importance of robust knowledge graph development and the practical differences between different semantic approaches (taxonomies vs ontologies). * Organise technical alignment meetings and supervise/mentor junior staff. * Make ethical decisions in your role, embedding the University's sustainability strategy into your working activities wherever possible. * Carry out other duties, commensurate with the grade and remit of the post, Experience applying version control (e.g., Git), continuous integration, or open-source practices specifically tailored to ontology development, model lifecycle management, or semantic data collaboration. ## Related Videos - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [ChatGPT and Java: A Match Made in Heaven or Hell?](https://www.wearedevelopers.com/videos/536-chatgpt-and-java-a-match-made-in-heaven-or-hell) - [Putting the Graph In GraphQL With The Neo4j GraphQL Library](https://www.wearedevelopers.com/videos/257-putting-the-graph-in-graphql-with-the-neo4j-graphql-library) - [New AI-Centric SDLC: Rethinking Software Development with Knowledge Graphs](https://www.wearedevelopers.com/videos/1417-new-ai-centric-sdlc-rethinking-software-development-with-knowledge-graphs) - [Knowledge graph based chatbot](https://www.wearedevelopers.com/videos/754-knowledge-graph-based-chatbot) - [Your organization as a Graph](https://www.wearedevelopers.com/videos/2051-your-organization-as-a-graph) ## Related Articles - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [What is Software Engineering?](https://www.wearedevelopers.com/magazine/289-what-is-software-engineering) - [Is Software Engineering Over-Saturated?](https://www.wearedevelopers.com/magazine/418-is-software-engineering-over-saturated) - [The Most Popular IT Jobs on the Market](https://www.wearedevelopers.com/magazine/376-the-most-popular-it-jobs-on-the-market) - [Software Engineer Salary London](https://www.wearedevelopers.com/magazine/252-software-engineer-salary-london)