Semantic Data Engineer: RDF/OWL, SPARQL & Knowledge Graphs

EUROPEAN DYNAMICS Group; United States; Remote; USD 100,000 - 180,000; Full time

Benefits offered by this job

Private Health Coverage

Flexible Working Hours

Professional Development

Career Growth

Dynamic Work Environment

Job summary

EUROPEAN DYNAMICS Group seeks a Semantic / Data Engineer to support a platform built around RDF data models, SPARQL queries, and structured datasets. You will understand, maintain, and evolve the semantic layer while collaborating with backend engineers and architects.

The role suits someone who enjoys data modelling, semantics, and knowledge representation in real-world production systems, with a focus on data quality, interoperability, and scalable data workflows.

Qualifications

• 3+ years of experience working with semantic or data-centric systems.
• Experience with RDF, RDFS, OWL, SPARQL.
• Ability to analyse existing models and understand implicit domain logic.

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.

Skills

SPARQL & RDF

Data modelling & ontology design

Knowledge graphs

Python scripting

Tools

Triplestores/Graph DBs

Apache Airflow

Job description

EUROPEAN DYNAMICS Group seeks a Semantic / Data Engineer to support a platform built around RDF data models, SPARQL queries, and structured datasets. You will understand, maintain, and evolve the semantic layer while collaborating with backend engineers and architects.

The role suits someone who enjoys data modelling, semantics, and knowledge representation in real-world production systems, with a focus on data quality, interoperability, and scalable data workflows.