Knowledge Graph Engineer (Life Sciences)

Capgemini; Vila Nova de Gaia; Híbrido; EUR 60.000 - 85.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Hybrid work

Health and life insurance

Training and certifications programs

Referral program with bonuses

Descripción de la vacante

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.

Formación

• 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.

Responsabilidades

• 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.

Conocimientos

Python

SQL

RDF/OWL/SPARQL

SHACL

Ontology modelling

Data engineering

Git

Educación

MSc/PhD in biology/biomedical sciences or related field

Herramientas

RDFLib

OWLReady2

GraphDB

Neo4j

Descripción del empleo

# Knowledge Graph Engineer (Life Sciences)Évora, Fundão, Lisboa - Expo, VNG - Cais GaiaApply for this job* Permanent* Experienced Professionals* Data & AI* ID 577846-en\\_US##**CAPGEMINI ENGINEERING**At Capgemini Engineering, the world leader in engineering services, we bring together a global team of engineers, scientists, and architects to help the world’s most innovative companies unleash their potential. From autonomous cars to life-saving robots, our digital and software technology experts think outside the box as they provide unique R&D and engineering services across all industries. Join us for a career full of opportunities. Where you can make a difference. Where no two days are the same.**YOUR ROLE**You will build and maintain the scientific knowledge graph content that will be used to answer scientific questions. You turn biological concepts into ontology-aligned RDF models, write the Python pipelines that generate them, and keep every assertion traceable to its source and evidence. You bridge scientific meaning and technical delivery, so that graph assets are accurate, governed and usable by analytics and AI applications.Key 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 or equivalent)* Collaborate with scientists and ontology specialists to resolve terminology, modelling and data-quality questions* Document mapping rules, modelling decisions and validation rules* Support the integration of graph assets into downstream data, analytics and AI solutions##**YOUR PROFILE*** MSc or PhD (or equivalent professional experience) in biology, biomedical sciences, bioengineering, genetics, neuroscience, bioinformatics, computational biology or a related field* 3 to 5 years of experience in data engineering, software engineering, semantic technologies or scientific data work* Strong Python and data manipulation skills, and a working command of SQL* Practical RDF modelling (subject, predicate, object) and hands-on experience with OWL, SPARQL and SHACL, plus RDFS or triple stores* Experience designing source-to-ontology mappings or integrating multiple scientific data sources* Practical experience using or developing ontologies, taxonomies, controlled vocabulary or knowledge graphs* Understanding of provenance, metadata, data quality and schema validation* Experience with biological or biomedical datasets* Git and modern software development practices* Clear communication with scientific and technical stakeholders* Fluent English* Preferred qualifications + Hands-on experience with Gene Ontology, MONDO, HPO, EFO, UBERON, ChEBI or other OBO Foundry ontologies + Semantic-web libraries such as RDFLib or OWLReady2 + Entity linking, terminology mapping or controlled vocabulary management + RDF-star, named graphs or property graph modelling (Neo4j, GraphDB) + Knowledge of FAIR principles, scientific metadata governance and LinkML + Agentic AI experience & LLM-based agents, retrieval-augmented generation, information extraction or LLM-assisted mapping, with validation of the output + Exposure to graph analytics, semantic similarity, machine learning or generative AI + APIs, Docker, cloud platforms, workflow orchestration and automated data pipelines + Experience in pharmaceutical & healthcare or another regulated environment + Portuguese fluency* What we look for + Scientific curiosity paired with engineering discipline + Critical thinking and attention to data provenance and quality + Comfort with ambiguity, and the ability to move between scientific meaning and technical implementation + An impact-driven mindset in a fast-paced environment**WHAT YOU'LL LOVE ABOUT WORKING HERE*** Join a multicultural and inclusive team environment.* Enjoy a supportive atmosphere promoting work-life balance.* Engage in exciting national and international projects.* Hybrid work.* Your career growth is central to our mission. Our array of career growth programs and diverse professionals are crafted to support you in exploring a world of opportunities.* Training and certifications programs.* Health and life insurance.* Referral program with bonuses for talent recommendations.* Great office locations.