Life Sciences Knowledge Graph Engineer - Hybrid & Growth

Capgemini; Évora; Hybrid; EUR 32,000 - 52,000; Full time

Benefits offered by this job

Hybrid work

Training programs

Health and life insurance

Referral program with bonuses

Great office locations

Job summary

Capgemini Engineering is seeking a skilled data and semantic technologies engineer to build and maintain a scientific knowledge graph. You will convert biological concepts into RDF models, develop Python pipelines, and ensure traceability to sources and evidence for analytics and AI applications.

You will work with scientists to resolve terminology, validate mappings to ontologies like GO, MONDO and HPO, and implement quality checks. Hybrid work and international opportunities are offered.

Qualifications

• MSc or PhD in biology, biomedical sciences, bioengineering, genetics, neuroscience, bioinformatics or related field.
• 3–5 years in data engineering, software engineering, semantic technologies or scientific data work.
• Strong Python and data manipulation skills with SQL knowledge.
• Experience with RDF modelling (OWL, SHACL) and SPARQL; provenance and quality emphasis.
• Knowledge of ontologies, taxonomies and knowledge graphs; source-to-ontology mapping.

Responsibilities

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

Skills

Python

SPARQL

RDF/OWL

SQL

Data manipulation

Git

Communication

English fluency

Education

MSc/PhD in biology or related field

Tools

OWL

SHACL

RDFLib

Neo4j/GraphDB

Job description

Capgemini Engineering is seeking a skilled data and semantic technologies engineer to build and maintain a scientific knowledge graph. You will convert biological concepts into RDF models, develop Python pipelines, and ensure traceability to sources and evidence for analytics and AI applications.

You will work with scientists to resolve terminology, validate mappings to ontologies like GO, MONDO and HPO, and implement quality checks. Hybrid work and international opportunities are offered.