Semantic Data & Knowledge Graph Engineer

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

• Design RDF-based data models, schemas and reusable semantic structures.
• Map structured and unstructured data to controlled vocabularies and ontologies.
• Develop Python pipelines for data transformation, entity resolution and RDF generation.
• Define and validate semantic relationships, identifiers, provenance and evidence.
• Write SPARQL queries to explore, test and analyse knowledge graphs.
• Implement automated semantic quality checks and mapping validation.
• Collaborate with subject matter experts to translate domain concepts into technical models.
• Produce clear documentation covering mappings, modelling decisions and validation rules.
• Support the integration of semantic assets into downstream data, analytics and AI solutions.

YOUR PROFILE

• Academic or professional background in Bioinformatics, Computational Biology, Life Sciences, Biomedical Engineering or a related discipline.
• 2–5 years of experience in data engineering, software engineering, semantic technologies or a related field.
• Strong Python programming and data manipulation skills.
• Practical understanding of RDF subject–predicate–object modelling.
• Experience with at least some of the following:
• RDF and RDFS
• OWL
• SPARQL
• SHACL
• Triple stores or RDF graph databases
• Experience mapping source data to canonical identifiers, vocabularies or semantic models.
• Understanding of provenance, metadata, data quality and schema validation.
• Experience with Git and modern software development practices.
• Strong written and verbal English communication skills.
• Familiarity with Life Sciences ontologies such as Gene Ontology, MONDO, HPO, EFO, UBERON, ChEBI or related standards.
• Experience with entity linking, terminology mapping or controlled vocabulary management.
• Knowledge of semantic-web libraries such as RDFLib, OWLReady2 or equivalent tools.
• Familiarity with cloud platforms, APIs, Docker and automated data pipelines.
• Exposure to knowledge-graph applications in search, analytics, Machine Learning or Generative AI

What You´ll Love About Working Here

Join a multicultural and inclusive team environment.

Enjoy a supportive atmosphere promoting work life balance.

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.

Access valuable training and certifications in cutting edge technologies.

Engage in exciting national and international projects.

Health and life insurance.

Referral program with bonuses for talent recommendations.

Great office locations.

About Capgemini

Capgemini is an AI-powered global business and technology transformation partner, delivering tangible business value. We imagine the future of organizations and make it real with AI, technology, and people. With our strong heritage of nearly 60 years, we are a responsible and diverse group of 420,000 team members in more than 50 countries. We deliver end-to-end services and solutions with our deep industry expertise and strong partner ecosystem, leveraging our capabilities across strategy, technology, design, engineering and business operations.