Senior Data Engineer - Ontology & Knowledge Graphs

present of AI; Greater London; Hybrid; GBP 95,000 - 130,000; Full time

Job summary

Valarian Technologies in London is seeking a Senior Data Engineer to turn messy information from many sources into clean, connected data that applications and AI tools can rely on. You will craft robust ontologies, enforce versioning, and optimize graph data pipelines using Python and SQL.

You’ll work in secure environments feeding an AI platform, ensuring provenance and permission rules are preserved as data moves from sources to derived outputs.

Qualifications

• Experience turning messy data into clean, connected data.
• Design ontologies with clear definitions and versioning.
• Production experience with a graph database or triple store.
• Skills in entity resolution and provenance tracking.

Responsibilities

• Build knowledge graphs to support AI platform workflows.
• Ensure permission-preserving data models across derived data.
• Collaborate with teams to improve data quality and governance.
• Maintain traceability of data origins and changes.

Skills

Python

SQL

Graph DB

Ontology design

Versioning

Entity matching

Provenance tracking

Neo4j

RDF store

Tools

Neo4j

RDF store

Job description

Senior Data Engineer - Ontology & Knowledge Graphs

AI & Data · London · Full time · Senior level

This role is about turning messy information from many places into clean, connected data that applications and AI tools can rely on. A strong candidate writes solid Python and SQL, has run a graph database or triple store in production, and has designed ontologies with clear definitions and versioning. Handling duplicate records, conflicting sources, and permissions that must carry through to derived data matters as much as the modelling itself.

How it fits the AI era

AI tools can speed up routine pipeline code, draft schema ideas, and help match records, but a knowledge graph is only useful if its facts can be trusted. Judgement about what an entity really is, how to handle uncertain or conflicting sources, and how to keep access rules intact stays with people. Here the graph also feeds AI assistants, so traceable answers and tested data quality directly shape how reliable those tools are.

How it builds AI experience

The work sits underneath an AI platform used inside secure, controlled environments, so the experience gained is in giving AI systems structured, permission-aware context and traceable results. Someone could prepare by building a small knowledge graph in Neo4j or an RDF store, then connecting it to a retrieval tool that cites where each answer came from. Practice with entity matching and provenance tracking would be especially relevant.

Worth showing

• Production graph database work
• Ontology design with versioning
• Entity resolution and provenance
• Permission-preserving data models

This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.

Valarian Technologies builds sovereign digital infrastructure that enables organizations to operate artificial intelligence and sensitive workloads inside environments under their direct control, acco