Senior Semantic Engineer

Location: Greater London

What we're looking for

The Senior Semantic provides the technical and operational capability that supports the enterprise semantic and ontology function.

Working closely with the Ontology Manager, the role is responsible for discovering, analysing, transforming, validating and publishing semantic assets derived from enterprise data, metadata, reference data and external information sources. The role supports the development and maintenance of ontologies, taxonomies, controlled vocabularies, business glossaries and knowledge graph assets.

The role acts as the bridge between enterprise data sources, metadata platforms and semantic assets, applying semantic technologies, data analysis, automation and modern AI-assisted techniques to support the delivery of governed, reusable and business-aligned semantic assets.

The role is responsible for the preparation, transformation, validation and publication of semantic assets but does not own enterprise application development, infrastructure management, platform administration, enterprise integration services or production data engineering.

What will you be doing Semantic Discovery & Data Analysis (40%) Relational Data Discovery

• Query and analyse enterprise databases to profile source systems, inspect schema structures and identify candidate business concepts, classifications and reference data.
• Work with business and technical stakeholders to understand the meaning, usage and context of source data assets.
• Identify semantic modelling opportunities within operational and analytical data sources.

Concept Discovery & Knowledge Extraction

• Analyse structured, semi-structured and unstructured information sources to identify candidate concepts, relationships and classifications.
• Utilise AI-assisted tooling, natural language processing techniques and analytical approaches to accelerate concept discovery and semantic enrichment activities.
• Support the identification of semantic duplication, inconsistencies and data quality issues requiring governance review.

Data Wrangling & Semantic Preparation

• Cleanse, standardise and reconcile terminology, hierarchies, classifications and reference data from multiple sources.
• Transform legacy vocabularies, spreadsheets and business classifications into reusable semantic assets.
• Maintain supporting datasets used in ontology, taxonomy and glossary development activities.

Semantic Asset Delivery & Knowledge Graph Enablement (40%) Semantic Modelling Support

• Develop and maintain RDF, SKOS, OWL, Turtle and JSON-LD representations of approved semantic models.
• Create mappings between business concepts, source data and semantic representations.
• Support ontology, taxonomy and controlled vocabulary publication processes.

SPARQL & Graph Operations

• Develop, test and optimise SPARQL queries to support semantic analysis, validation, reporting and knowledge graph operations.
• Support concept scheme maintenance and semantic asset lifecycle activities within enterprise graph platforms.
• Assist with semantic publication and synchronisation activities across approved platforms.

Entity Resolution & Identifier Management

• Implement and maintain URI minting standards and identifier management practices.
• Support synonym management, concept reconciliation and entity matching activities.
• Establish and maintain mappings between internal semantic assets and relevant external standards, classifications and reference datasets.

Semantic Validation & Quality Assurance

• Develop and maintain SHACL validation rules and semantic quality controls.
• Execute semantic testing, compliance reviews and impact assessments.
• Monitor semantic assets for adherence to modelling standards, governance requirements and quality expectations.

Metadata & Semantic Operations (20%) Metadata Integration

• Support the publication and synchronisation of semantic assets within metadata, glossary and governance platforms.
• Maintain links between semantic assets, business glossaries and metadata catalogues.
• Contribute to semantic lineage, classification and metadata management activities.

Semantic Asset Lifecycle Management

• Maintain ontology and semantic asset repositories using Git and Git Hub.
• Support Ontology CI/CD processes, including automated validation, testing, release packaging and version management.
• Contribute to semantic asset release, publication and change management activities.

Stakeholder Collaboration

• Collaborate with domain experts, business analysts, architects and engineering teams to clarify business terminology, definitions and…