Senior Data Engineer - Ontology & Knowledge Graphs
Senior Data Engineer at Valarian (London, office-first hybrid) building the data foundations for its secure enterprise AI platform: defining ontologies, resolving entities, and building ingestion/transformation pipelines in Python and SQL to serve graph, relational and NoSQL data models (Neo4j/Cypher, RDF/SPARQL) powering AI tools and applications.
- Compensation
- Not disclosed
- Location
- London, United Kingdom
- Work setup
- Hybrid
- Seniority
- Senior
- Employment
- Not specified
- Experience
- Not specified
- Category
- Data engineering
- Posted
Skills
Must have
- Strong production Python engineering; building maintainable, tested ingestion and transformation pipelines
- Strong SQL: relational modelling, transactions, indexing, migrations, query optimisation
- Practical NoSQL experience: document or key-value modelling, indexing, consistency trade-offs
- Production experience designing, populating and querying a graph database or triple store (e.g. Neo4j/Cypher, RDF store/SPARQL)
- Practical ontology design: entity definitions, stable identifiers, relationship semantics, controlled vocabularies, constraints, versioning
- Understanding of property graphs and RDF-based knowledge graphs and when each is appropriate
- Experience integrating heterogeneous sources, resolving entity identity, maintaining provenance and lineage
- Experience handling incremental updates, deletions, schema changes and automated data validation
- Ability to translate ambiguous domain requirements into documented models, queries and reliable data interfaces
Full description
Valarian: A New Era of Sovereign Intelligence
Valarian is a dual use technology company building critical tools to safeguard the future in an era of evolving global security challenges. Backed by a Series A funding round of $50m led by NEA, we are rethinking security beyond traditional military domains to address asymmetric threats that impact our technological advantage, economic strength, and democratic institutions. We provide the control infrastructure that allows government and regulated enterprise to put frontier-class AI to work safely.
We are bringing a frontier AI experience inside secure boundaries for the first time. Our technology supports mission critical workflows across government, healthcare, and enterprise, including:
- Scaling open-weight models without external inference endpoints.
- Putting frontier class AI to work across organisations through partnerships with other leading AI startups such as Perplexity.
- Increasing operational resiliency for air gapped, on prem, and cloud based systems.
- Securing intellectual property and maintaining auditability for high stakes enterprise environments.
- Facilitating secure information flow during disaster response, M&A due diligence, and privileged legal communications.
We’ve only scratched the surface. Built in Britain by veterans of the Ministry of Defence, British Forces, Darktrace, and elite engineering backgrounds, we are driven by a shared mission to safeguard western democracy. Whether you join our London HQ or our wider global organisation, you’ll be part of a collaborative, high performing team creating the cutting edge software and infrastructure that defines the frontier of enterprise AI.
The Role
You will design and build the data foundations that allow ACRA applications and Valarie to understand organisational information. Your work will turn heterogeneous sources into coherent entities, relationships and queryable data products across graph, relational and NoSQL databases.
What you’ll do:
- Work with product teams and domain experts to define and evolve ontologies covering organisational entities, relationships, classifications and business rules.
- Build ingestion and transformation pipelines from APIs, databases, documents, files and events into canonical data models.
- Implement entity resolution, deduplication and source reconciliation, retaining provenance and handling conflicting or uncertain information.
- Design and maintain graph models, relational schemas and NoSQL structures, choosing representations according to query and consistency requirements.