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Linked Data Engineer
IQ Staffing B.V.
About the role
Linked Data Engineer — Knowledge Graphs & Semantic Modelling
Semantic data modelling at enterprise scale, which is a narrower craft than "data engineer" and a considerably more interesting one. You'll build the linked data pipelines, map relational, XML and JSON sources onto semantic models, and work with the ontologies that let data from completely different corners of an organisation actually talk to each other.
It's a role with room to specialise. Linked data expertise is scarce, and this is an environment where you'd deepen it rather than dabble.
The environment
Our client is a large financial organisation treating data as a strategic asset rather than a by-product. You'd join the platform team responsible for data modelling and governance, which delivers standardised, reusable and interoperable data to domains across the organisation through knowledge graph and linked data solutions.
You'll work alongside tech leads, product owners and data stewards, in a setting where data mesh principles shape how domains own and share their data products.
What you'll do
Develop and maintain linked data pipelines using RDF.
Design mappings from relational, XML and JSON sources to semantic models.
Implement data quality rules with SHACL.
Work with enterprise ontologies and vocabularies.
Build APIs that expose semantic data and metadata.
Integrate domain data products in line with data mesh principles.
Contribute to CI/CD pipelines, and document the models and pipelines properly.
Tech stack
Core: RDF · RDFS · OWL · SPARQL · SHACL · triple stores · Python or Java · REST APIs
Also in the mix: RML / YARRRML · GraphQL · Neo4j and Cypher · Kafka or Event Hubs · Azure · Azure DevOps · JSON, XML and CSV
What you'll bring
Must-haves
Two to five years in data, software or knowledge engineering, in an enterprise setting.
Solid grounding in RDF, RDFS, OWL and SPARQL.
Hands-on experience with triple stores — GraphDB, Stardog, Amazon Neptune, Virtuoso or Blazegraph.
SHACL validation used in practice, not just read about.
Programming in Python, Java or similar, plus REST API and system integration experience.
A real understanding of data modelling, metadata, ontologies and knowledge graphs, and comfort across JSON, XML and CSV.
Nice to have
RML or YARRRML for mapping.
Labeled property graphs and Cypher queries (Neo4j).
Kafka or Event Hubs.
GraphQL.
Azure cloud services, Git and CI/CD basics.
Data mesh concepts and enterprise data governance.
Agile/Scrum experience.
A background in financial services.
You're precise about definitions — in this field, a sloppy one propagates — and you like work where the payoff is other people finding and reusing data they didn't know existed.
Good to know
The role is hybrid, based in the Utrecht region.
A pre-employment screening is part of the process — standard for the financial sector.
You'll need a valid EU work permit or existing right to work in the Netherlands.