Knowledge graph engineer (life sciences)

Sobre a vaga

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.

O que vais fazer

• 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

O que é pedido

• 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

Valorizado

• 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

O que é oferecido

• Join a multicultural and inclusive team environment
• Enjoy a supportive atmosphere promoting work-life balance
• Engage in exciting national and international projects
• Hybrid work
• Career growth programs
• Training and certifications programs
• Health and life insurance
• Referral program with bonuses for talent recommendations
• Great office locations

✸ Benefícios e vantagens (8)

• Acções da empresa
• Comida, fruta e bebida
• Flex benefits
• Flexibilidade de horário
• Mais de 22 dias de férias
• Programa de descontos
• Seguro de saúde
• Suporte psicológico

✸ Valores e cultura (9)

• Ambiente internacional
• Crenças e religião
• Híbrido
• Igualdade de género
• Igualdade racial
• Incentivo à criatividade & inovação
• LGBTQ+ friendly
• Pessoas portadoras deficiência / incapacidade permanente
• Tecnologias de ponta

Processo de entrevista

O processo de entrevista da Capgemini Engineering é totalmente remoto. Este conta com as seguintes fases:

1. Em primeiro lugar, serás convidada/o para uma reunião com um elemento da nossa equipa de Talent Acquisition;
2. Depois, o processo terá continuidade por via de uma entrevista técnica, com um dos nossos experts ou, através de um assessment test; Caso necessário, poderás ser também convidada/o a participar numa entrevista com o cliente;
3. Por fim, ser-te-á apresentada uma proposta de colaboração.

Boa sorte!

Quanto paga este cargo

Este anúncio não mostra o salário

Investimento de tempo

1 h 26 min Investimento de tempo em entrevistas

Índice de dificuldade das entrevistas

43/100