Knowledge Graph Engineer – Life Sciences (Hybrid)

Capgemini Engineering; Évora; Hybrid; EUR 40,000 - 65,000; Full time

Benefits offered by this job

Hybrid work

Health and life insurance

Training and certifications

Career growth programs

Referral program with bonuses

Great office locations

Job summary

Capgemini Engineering in Évora, Portugal, seeks a data/semantic engineer to build and maintain a scientific knowledge graph. You will transform biological concepts into RDF models, write Python pipelines, and ensure provenance and evidence are traceable for analytics and AI applications.

You will design semantic data structures, map data to ontologies, and collaborate with scientists to ensure data quality. Hybrid work and international projects are offered.

Qualifications

• MSc or PhD in biology or related field.
• 3–5 years in data engineering, semantic technologies or scientific data work.
• Strong Python and SQL skills.
• Experience with RDF modelling and SHACL.
• Knowledge of ontologies and knowledge graphs.

Responsibilities

• Design RDF-based data models and semantic structures for genes, proteins, diseases, phenotypes, compounds and experiments.
• Map data to controlled vocabularies and ontologies.
• Develop Python pipelines for data transformation, entity resolution and RDF generation.
• Define identifiers, relationships, provenance and evidence.
• Write SPARQL queries to explore knowledge graphs.
• Implement semantic quality checks and mapping validation.
• Collaborate with scientists and ontology specialists on terminology and data quality.
• Document mapping rules and validation rules.
• Support integration of graph assets into downstream data, analytics and AI solutions.

Skills

Python

SQL

RDF/OWL/SPARQL

Data engineering

Ontology modelling

Git

English fluency

Data provenance

Version control

Education

MSc/PhD in biology or related field

Tools

OWL

SPARQL

SHACL

RDFLib

Neo4j

Job description

Capgemini Engineering in Évora, Portugal, seeks a data/semantic engineer to build and maintain a scientific knowledge graph. You will transform biological concepts into RDF models, write Python pipelines, and ensure provenance and evidence are traceable for analytics and AI applications.

You will design semantic data structures, map data to ontologies, and collaborate with scientists to ensure data quality. Hybrid work and international projects are offered.