Knowledge Graph Engineer, R&D Data Science

At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn more at

Job Function
Data Analytics & Computational Sciences

Job Sub Function
Data Science

Job Category
Scientific/Technology

All Job Posting Locations:
Cornellà de Llobregat, Barcelona, Spain, Madrid, Spain

Job Description
Johnson & Johnson Innovative Medicine is recruiting for a
Knowledge Graph Engineer, R&D Data Science & Digital Health - Data Strategy and Products
. The primary location is Barcelona or Madrid, Spain but is also open to Titusville, NJ; Spring House, PA; or Cambridge, MA.

Our expertise in Innovative Medicine is informed and inspired by patients, whose insights fuel our science-based advancements. Engineers like you work on teams that save lives by developing the medicines of tomorrow.

Join us in developing treatments, finding cures, and pioneering the path from lab to life while championing patients every step of the way.

Learn more at

Job Responsibilities
We are committed to using innovative technology to improve healthcare outcomes worldwide. As part of this mission, we are seeking a Knowledge Graph Engineer to join our Data Strategy and Products team to standardize and connect biomedical and clinical data. You will be a hands-on technical contributor with depth in semantic technologies, ontology, and graph data modeling, plus strong familiarity with the life sciences domain.

You will connect enterprise master data with R&D data across the entire product lifecycle so trusted, interoperable knowledge powers analytics, search, and AI across Johnson and Johnson Innovative Medicine.

• Contribute to the design and implementation of a scalable knowledge graph infrastructure focused on data standardization and interoperability.
• Curate and extend ontologies for clear mapping into established biomedical ontologies and controlled terminologies using RDF standards.
• Apply graph-based data modeling for efficient organization, integration and retrieval to ensure system flexibility and long-term maintainability.
• Stand up SPARQL/GraphQL/REST services; develop ingestion and curation pipelines to ingest, normalize and map concepts across data sources.
• Extend and curate ontologies (e.g., diseases, drugs, targets, pathways, etc.) and maintain synonyms, cross-references, and provenance.
• Partner with cross-functional teams to enable NLP/RAG over graphs, features for predictive modeling and terminology services for search and study design tools.
• Work with IT and DevOps teams to deploy and manage the graph database infrastructure, focusing on high availability, scalability, and recovery operations.
• Create and be responsible for documentation, such as data dictionaries, data lineage, and data flow diagrams, to facilitate understanding of the knowledge graph.

Job Qualifications

• Desired Ph.D. or master's degree in bioengineering, computer science, IT, bioinformatics, physics, mathematics, or related fields, emphasis on semantic technologies and biomedical application.
• At least 5 years professional experience in health informatics, or at least 7 years of professional experience or with additional consideration for candidates with graduate degrees or equivalent experience.
• Programming background in parser combinators, natural language processing, and linked data (RDF Triple Stores and property graphs).
• Demonstrated experience in large-scale knowledge graphs construction, ontology development, pharmaceutical or healthcare domains integration.
• Proficiency in semantic web technologies (SPARQL, RDF, OWL), familiarity with graph databases (Neo4j, Amazon Neptune).
• Proven work with complex biomedical datasets, including genomics, proteomics, and high-throughput screening data.
• Impressive records in a pharmaceutical, biotech, or related research environment are preferred. Proficiency in various data storage solutions (SQL, key-value, column, document, graph stores) and data modeling techniques (semantic data, ontologies, taxonomies).
• Experience in CI/CD implementations, git usage, CI/CD stacks (Jenkins, GitLab, Azure DevOps), DevOps tools, metrics/monitoring, and containerization technologies (Docker, Singularity).
• Strong skills in analysis, problem-solving, organizational change, project delivery, and managing external vendors.
• Demonstrated agile decision-making, performance management, continuous learning, and commitment to quality.
• Ability to multi-task, prioritize work, exhibit organizational skills and flexibility to deliver maximum business value.
• Capacity to translate discussions into user requirements and project plans.
• Willingness to travel less than 25% to conferences and internal meetings.

#JNJDataScience