Job Description:

Johnson and Johnson Innovative Medicine (J& J IM), a pharmaceutical company of Johnson & Johnson is recruiting for a Senior Data Science Solution Architect. This position has a primary location of Barcelona, Spain. The secondary location is Madrid. This role is hybrid.

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 https: //www.jnj.com/innovative-medicine

Position Summary:

Senior Data Science Solution Architect will lead the design of scalable, governed, and AI-ready data systems that power data science and analytics across Discovery and Translational Research.

This role bridges scientific workflows, data platforms, and AI environments to create a unified, reproducible data foundation for R& D.

Key Responsibilities:

• Design and oversee the end-to-end data and workflow architecture, integrating Nextflow/Snakemake pipelines with AWS S3, Snowflake, and TileDB.

• Define standards and reference frameworks for pipeline structure, metadata, and governance integration.

• Collaborate with Data Transformation, AI/ML, and Governance teams to align architecture with scientific and enterprise strategy.

• Enable data scientists and AI tools to query harmonized datasets through scalable APIs and metadata-driven design.

• Evaluate and guide adoption of emerging data and AI technologies to ensure future-ready systems.

Qualifications:

• MS/PhD in Computer Science, Data Science, Bioinformatics, or related field.

• 5+ years of hands-on, industry experience building and managing production Nextflow pipelines (DSL2).

• Proven expertise in data or solution architecture for analytics or R& D.

• Proficiency with cloud data environments (AWS, Snowflake, TileDB).

• Strong understanding of data governance, FAIR principles, and compliance frameworks.

• Excellent collaboration and communication across science, engineering, and IT.

Strategic Impact:

• Unified, reproducible pipeline architecture adopted across Discovery & Translational research.

• Governed, AI-ready data accessible across modalities and teams.

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