Hybrid Knowledge Graph Engineer: Life Sciences Ontologies

Capgemini; Vila Nova de Gaia; Hybrid; EUR 60,000 - 85,000; Full time

Benefits offered by this job

Hybrid work

Health and life insurance

Training and certifications programs

Referral program with bonuses

Job summary

Capgemini Engineering seeks a Knowledge Graph Engineer for Life Sciences in Portugal. You will build and maintain scientific knowledge graphs, transform data with Python pipelines, and align concepts to ontologies, ensuring provenance and traceability for analytics and AI applications.

You will collaborate with scientists and ontology experts, validate mappings, and contribute to data quality and governance through SHACL checks and documentation. Hybrid work is offered.

Qualifications

• MSc or PhD (or equivalent) in biology, biomedical sciences, bioengineering, genetics, neuroscience, bioinformatics or related fields.
• 3–5 years in data engineering, software engineering, semantic technologies or scientific data work.
• Strong Python and data manipulation skills with SQL ability.
• Practical RDF modelling and hands-on experience with OWL, SPARQL and SHACL, plus RDFS or triple stores.
• Experience mapping data to ontologies and integrating multiple scientific data sources.
• Experience with ontologies, taxonomies, controlled vocabularies or knowledge graphs.
• Understanding of provenance, metadata, data quality and schema validation.
• Fluent English; Portuguese fluency is a plus.

Responsibilities

• Design RDF-based data models and reusable semantic structures for genes, proteins, diseases, phenotypes, compounds and experiments.
• Map structured and unstructured data to 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 and analyze knowledge graphs.
• Implement 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

SQL

RDF/OWL/SPARQL

SHACL

Ontology modelling

Data engineering

Git

Education

MSc/PhD in biology/biomedical sciences or related field

Tools

RDFLib

OWLReady2

GraphDB

Neo4j

Job description

Capgemini Engineering seeks a Knowledge Graph Engineer for Life Sciences in Portugal. You will build and maintain scientific knowledge graphs, transform data with Python pipelines, and align concepts to ontologies, ensuring provenance and traceability for analytics and AI applications.

You will collaborate with scientists and ontology experts, validate mappings, and contribute to data quality and governance through SHACL checks and documentation. Hybrid work is offered.