Principal Scientist, Data Science – R&D DSDH – Therapeutics Development & Supply

Johnson & Johnson

Data Scientist – Data Engineer designing and optimizing data systems for Therapeutics Development at Johnson & Johnson. Engaging with cross-functional teams to enable advanced analytics and AI applications in healthcare.

Posted 5/8/2026full-timeMadrid • 🇪🇸 SpainLeadWebsite

Tech Stack

Tools & technologies

Amazon RedshiftAWSCloudNoSQLPythonSQL

About the role

Key responsibilities & impact

Design, build, and maintain scalable data pipelines for acquiring, integrating, and managing TDS data from diverse data generation sources and systems.
Create and optimize data flows for structured and unstructured data using Python, R, SQL, cloud services, and other modern engineering tools.
Develop and maintain TDS‑specific data repositories, implementing enterprise‑level data models and creating new models as needed.
Enable AI/ML readiness by ensuring data is well‑structured, versioned, traceable, and semantically aligned with enterprise data standards.
Partner with data scientists, TDS domain experts, and digital technology teams to translate business needs into high‑quality data products and engineering requirements.
Engage with scientific, technical, and operations stakeholders to understand requirements, design data solutions, and drive adoption.

Requirements

What you’ll need

Advanced degree in Engineering, Data Science, Life Sciences, Computer Science, or related field; advanced degree preferred.
3+ years of experience in data engineering, including data modeling and database design, preferably in a scientific, manufacturing, or healthcare environment.
Proficiency with Python, R, SQL, and cloud-based architectures (e.g., AWS services, Snowflake, Redshift).
Experience with NoSQL and graph databases.
Strong analytical, problem‑solving, and stakeholder‑management skills, with the ability to translate discussions into actionable requirements.
Ability to drive multiple exciting projects simultaneous with strong organizational skills and adaptability.
Experience with regulated or standards‑driven data environments, such as CDISC, HL7, FHIR, OMOP, DICOM, or manufacturing/quality data standards (preferred).
Familiarity with high‑dimensional data (e.g., imaging, sensor data, etc) (preferred).

Benefits

Comp & perks

Included professional development
Flexible work environment

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

data engineeringdata modelingdatabase designPythonRSQLcloud-based architecturesNoSQLgraph databasesdata pipelines

Soft Skills

analytical skillsproblem-solvingstakeholder managementorganizational skillsadaptability

Certifications

advanced degree in Engineeringadvanced degree in Data Scienceadvanced degree in Life Sciencesadvanced degree in Computer Science