Vector Data Engineer

Barcelona - Spain

Monthly Salary: Not Disclosed

Posted on: 9 hours ago

Vacancies: 1 Vacancy

Job Summary

At Johnson & Johnsonwe believe health is everything. Our strength in healthcare innovation empowers us to build aworld where complex diseases are prevented treated and curedwhere treatments are smarter and less invasive andsolutions are 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 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 and Johnson Innovative Medicine (J&J IM) a pharmaceutical company of Johnson & Johnson is recruiting for a Vector Data Engineer. This position has a primary location of Barcelona Spain. The secondary location is Madrid. This is a hybrid role.

Our expertise in Innovative Medicine is informed and inspired by patients whose insights fuel our science-based advancements. Visionaries like you work in 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

Position Summary:

The Vector Data Engineer designs and implements the embedding and semantic-search infrastructure that connects discovery translational and clinical data into AI-ready knowledge representations.

This role bridges multi-omics data engineering and machine-learning infrastructure enabling scientists and agentic tools to discover biological insights through vector-based search and reasoning.

Key Responsibilities:

Develop scalable pipelines that convert multi-omics and clinical data (e.g. proteomics transcriptomics spatial omics biomarkers) into vectorized embeddings for AI and semantic retrieval.

Build and maintain vector databases and hybrid data stores using technologies such as TileDB Weaviate or Snowflake Cortex.

Collaborate with the Data Transformation Engineers to design standardized data formats suitable for embedding generation and cross-modality mapping.

Integrate metadata ontology terms and provenance into vector representations to ensure traceability and governance compliance.

Partner with AI/ML Team to deploy embeddings supporting agentic reasoning semantic similarity and cross-dataset query.

Optimize indexing retrieval and inference performance across large-scale multi-omics data collections.

Evaluate and incorporate emerging representation-learning and knowledge-graph techniques to improve data discoverability and model interoperability.

Qualifications:

MS/PhD in Computer Science Computational Biology Data Science or related field.

3 years of experience building or maintaining vector or semantic-retrieval infrastructure.

Hands-on experience with multi-omics or biomedical data integration (e.g. RNA-seq proteomics clinical endpoints).

Proficiency in Python and frameworks such as LangChain Transformers or sentence-embedding models.

Familiarity with TileDB Snowflake Weaviate FAISS or other vector/array database systems.

Understanding of metadata modeling ontologies (e.g. OBO UMLS) and FAIR data practices.

Strong ability to collaborate across solution architecture data science and AI/ML teams.

Strategic Impact:

Multi-omics and clinical data assets transformed into interoperable vectorized embeddings supporting scientific AI applications.

AI can perform semantic queries and reasoning over governed datasets.

Vector database infrastructure scales efficiently and complies with governance and lineage standards.

Accelerated insight generation across discovery translational and clinical domains.

#JRDDS

Required Skills:

Preferred Skills:

Advanced Analytics Business Intelligence (BI) Coaching Collaborating Critical Thinking Data Analysis Database Management Data Privacy Standards Data Reporting Data Savvy Data Science Data Visualization Econometric Models Process Improvements Technical Credibility Technologically Savvy Workflow Analysis