Semantic Data Engineer
Core
Build and maintain the semantic layer of a complex platform using RDF data models and SPARQL queries to support structured datasets and application flows.
Role type
Semantic Data Engineer
Builds
Semantic data models, vocabularies, and integrated application flows
Domain
Knowledge representation, semantic interoperability, and structured data management
Deliverable
production ML models | product features | dashboards & analysis | research | client delivery | infrastructure | physical/clinical work
Required skills
RDF/TTL data modeling, SPARQL query development, ontology design, data ingestion workflows, structured data format handling (XML, JSON, CSV), domain logic analysis
Preferred skills
Triplestore or graph database experience, EU data standards familiarity, Python scripting, Apache Airflow
Technologies
RDF, RDFS, OWL, SPARQL, TTL, XML, JSON, CSV, Python, Apache Airflow
Responsibilities
Analyse and maintain RDF/TTL data models and vocabularies; Develop, optimise, and maintain SPARQL queries; Support data ingestion, transformation, and validation workflows; Ensure consistency and correctness of semantic data across the platform; Collaborate with backend engineers to integrate semantic logic into application flows; Assist in documenting semantic models, assumptions, and constraints; Participate in troubleshooting data quality and reasoning issues
