At a Glance
- Tasks: Design and optimise graph schemas, manage ontologies, and enhance data workflows.
- Company: Join Rubicon Consulting, a leading talent management consultancy in Warwickshire.
- Benefits: Competitive pay, flexible working, and opportunities for professional growth.
- Other info: Dynamic role with a focus on collaboration and cutting-edge technology.
- Why this job: Lead innovative projects that shape the future of data architecture and AI.
- Qualifications: 7-12 years in graph databases and semantic modelling; strong technical skills required.
The predicted salary is between 80000 - 100000 £ per year.
Rubicon Consulting is currently recruiting for a Semantic Graph & Ontology Architect on a 6 Month Rolling Contract, based in Warwickshire.
Role Summary
We’re building a Smart Data Fabric that unifies enterprise data (Snowflake, SharePoint, ERP, NoSQL, and document silos) and exposes it to advanced AI agents through a semantic, graph-native, and vector-aware foundation. You will own graph and semantic architecture, modeling business relationships, processes, and logic to enable accurate, contextual, auditable workflows. This is a hands-on leadership role spanning LPG vs RDF/OWL tradeoffs, query optimization, and ontology engineering.
Key Responsibilities
- Graph & Semantic Architecture
- Design scalable graph schemas (LPG and/or RDF/OWL) based on semantic and inference requirements.
- Author and optimize Cypher/Gremlin/SPARQL queries for multi-hop traversal, orchestration, and complex reasoning.
- Define canonical entity models and mapping layers across Snowflake, MongoDB, SharePoint, ERP, and unstructured content.
- Ontology Engineering & Reasoning
- Create and maintain formal ontologies/taxonomies; govern versioning and lifecycle.
- Implement logical inference (rules/constraints) for agent decision-making, conflict detection, and workflow integrity.
- Establish semantic consistency standards and data quality checks.
- Hybrid Semantic Layer (Graph + Logic)
- Design a hybrid semantic layer combining graph context with business logic and access controls for semantic search, multi-hop traversal, and knowledge contextualization.
- Model RACI/RBAC as graph edges/nodes; embed compliance rules and auditability.
- APIs, Patterns & Collaboration
- Define clean API layers for semantic enrichment and retrieval; deliver reference implementations and patterns.
- Specify MCP-based (Model Context Protocol) tool discovery/invocation patterns; collaborate with platform engineers for agent connectivity.
- Partner with data/platform/security teams on ingestion pipelines, lineage, governance, and observability requirements.
- Quality, Performance & Governance
- Set query performance budgets; prevent Cartesian explosions; ensure index utilization.
- Establish lineage and data governance artifacts (semantic catalogs, policy nodes, audit trails).
- Document standards and mentor engineers adopting graph/semantic patterns.
Requirements
- Bachelor’s/Master’s in CS, Data Science, Mathematics, Engineering, or related field.
- 7–12 years in graph databases, semantic modelling, ontology engineering.
- Deep expertise in Cypher, Gremlin, SPARQL; strong command of LPG vs RDF/OWL tradeoffs.
- Hands-on with Neo4j, AWS Neptune, TigerGraph, Stardog (at least one in production).
- Experience mapping enterprise data (Snowflake/MongoDB/SharePoint/ERP) into graph/ontology layers.
- Strong understanding of RBAC/RACI, data governance, lineage, and security controls.
- Ability to design clean APIs and reference implementations for semantic enrichment/retrieval.
- Practical AWS familiarity (IAM, VPC, S3, EKS/ECS/Lambda) in collaboration with platform teams.
Preferred Qualifications
- Ontology tooling (Protégé, SHACL/SWRL), reasoning engines, and constraint modeling.
- Prior delivery of enterprise knowledge graphs supporting workflows & audit trails.
- Exposure to vector retrieval/RAG and how graph context informs re-ranking.
- Observability awareness (tracing across graph layers, OpenTelemetry, Prometheus/Grafana).
- Experience with Snowflake/MongoDB/SharePoint APIs and ERP data structures.
Our Company
Rubicon Consulting is a Talent management consultancy which helps you to optimise business performance and competitive advantage by choosing the right people first time.
Semantic Graph & Ontology Architect employer: Rubicon Consulting
Rubicon Consulting is an exceptional employer, offering a dynamic work environment in Warwickshire where innovation meets collaboration. With a strong focus on employee growth and development, we provide opportunities for hands-on leadership in cutting-edge projects like our Smart Data Fabric initiative. Our culture promotes creativity and teamwork, ensuring that every team member can contribute meaningfully while enjoying the benefits of a supportive and forward-thinking workplace.
StudySmarter Expert Advice🤫
We think this is how you could land Semantic Graph & Ontology Architect
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at local meetups. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects related to graph databases and ontology engineering. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on common questions related to semantic architecture and query optimisation. Practise explaining complex concepts in simple terms – it shows you really understand your stuff!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities, and applying directly can sometimes give you an edge. Plus, it’s super easy to keep track of your applications that way.
We think you need these skills to ace Semantic Graph & Ontology Architect
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter for the Semantic Graph & Ontology Architect role. Highlight your experience with graph databases and ontology engineering, and don’t forget to mention any relevant projects that showcase your skills!
Showcase Your Technical Skills:We want to see your hands-on experience! Be specific about the technologies you've worked with, like Cypher, Gremlin, or Neo4j. Mention any successful implementations or optimisations you've achieved in previous roles.
Be Clear and Concise:When writing your application, keep it straightforward. Use clear language and avoid jargon unless it's relevant to the role. We appreciate a well-structured application that gets straight to the point!
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. We can’t wait to hear from you!
How to prepare for a job interview at Rubicon Consulting
✨Know Your Graphs
Make sure you brush up on your knowledge of graph schemas, especially LPG and RDF/OWL. Be ready to discuss how you've designed scalable graph architectures in the past and how you approach query optimisation using Cypher, Gremlin, or SPARQL.
✨Showcase Your Ontology Skills
Prepare examples of formal ontologies or taxonomies you've created and maintained. Discuss how you've implemented logical inference for decision-making and ensured semantic consistency in your previous roles.
✨API Mastery is Key
Be ready to talk about your experience defining clean API layers for semantic enrichment and retrieval. Highlight any reference implementations you've delivered and how they improved data accessibility and governance.
✨Collaboration is Crucial
Rubicon Consulting values teamwork, so come prepared to discuss how you've partnered with data, platform, and security teams in the past. Share specific examples of how your collaboration led to successful ingestion pipelines and data governance.
