Semantic Graph & Ontology Architect

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Are you passionate about transforming enterprise data into meaningful insights? Do you thrive in innovative environments where you can shape the future of data architecture? If so, our client is looking for you! Join us as a Semantic Graph & Ontology Architect and play a pivotal role in developing a Smart Data Fabric that unifies various data sources like Snowflake, SharePoint, and ERP systems, all while enhancing AI capabilities through a sophisticated semantic, graph-native foundation.

Role: Semantic Graph & Ontology Architect

Duration: 6 Months (extension options)

Location: Fully Remote

Rate: £ Competitive (outside ir35)

How You'll Make an Impact:

As a hands-on leader, you will:

Graph & Semantic Architecture:

Design scalable graph schemas (LPG and/or RDF/OWL) to meet semantic and inference requirements.
Author and optimise queries using Cypher, Gremlin, and SPARQL for seamless data traversal and reasoning.
Define canonical entity models and mapping layers to integrate diverse data sources.Ontology Engineering & Reasoning:

Create and maintain formal ontologies and taxonomies while governing their versioning and lifecycle.
Implement logical inference for agent decision-making and ensure workflow integrity.
Establish standards for semantic consistency and data quality checks.Hybrid Semantic Layer (Graph + Logic):

Design a hybrid semantic layer that combines graph context with business logic for enhanced search and knowledge contextualization.
Model RACI/RBAC as graph edges/nodes, embedding compliance rules for auditability.APIs, Patterns & Collaboration:

Define clean API layers for semantic enrichment and retrieval; deliver reference implementations.
Collaborate with platform engineers for agent connectivity and tool discovery patterns.
Partner with data, platform, and security teams for governance and observability.Quality, Performance & Governance:

Set performance budgets to ensure efficient query execution and prevent issues.
Establish lineage and governance artefacts like semantic catalogues and audit trails.
Document standards and mentor engineers in adopting graph and semantic patterns.What You Bring:

A bachelor's or master's degree in computer science, Data Science, Mathematics, Engineering, or a related field.
7-12 years of experience in graph databases, semantic modelling, and ontology engineering.
Expertise in query languages like Cypher, Gremlin, and SPARQL, with a strong understanding of LPG vs RDF/OWL tradeoffs.
Hands-on experience with Neo4j, AWS Neptune, TigerGraph, or Stardog in a production environment.
Proficiency in mapping enterprise data (Snowflake, MongoDB, SharePoint, ERP) into graph and ontology layers.
A solid grasp of RBAC/RACI, data governance, lineage, and security controls.
Ability to design clean APIs for semantic enrichment and retrieval.
Familiarity with AWS services (IAM, VPC, S3, EKS/ECS/Lambda) in collaboration with platform teams.Preferred Qualifications:

Experience with ontology tooling (Protégé, SHACL/SWRL) and reasoning engines.
Prior delivery of enterprise knowledge graphs supporting workflows and audit trails.
Exposure to vector retrieval and how graph context informs data re-ranking.
Knowledge of observability tools like OpenTelemetry, Prometheus, and Grafana.Why Join Us?

This is your opportunity to be at the forefront of data innovation in the energy sector! If you are eager to make a significant impact and collaborate with talented professionals, we want to hear from you! Apply now and embark on a journey to redefine how data drives decision-making in our client's organisation.

Let's build a smarter future together!

How to Apply:
If you're excited about this opportunity and believe you're a great fit, please answer screening questions during application and submit your CV.

Join our client and help shape the future of data engineering! We can't wait to welcome you aboard!

Candidates will ideally show evidence of the above in their CV to be considered.

Please be advised if you haven't heard from us within 48 hours then unfortunately your application has not been successful on this occasion, we may however keep your details on file for any suitable future vacancies and contact you accordingly.

We use generative AI tools to support our candidate screening process. This helps us ensure a fair, consistent, and efficient experience for all applicants. Rest assured, all final decisions are made by our hiring team, and your application will be reviewed with care and attention