Hybrid Principal Scientist, Data Science – Data Quality

at Johnson & Johnson

• Job title: Principal Scientist, Data Science – Data Quality
• Job type: Full Time
• Experience level: Lead
• Salary: Not specified
• Degree requirement: Bachelor's Degree
• Tech skills: Google Cloud Platform, Python, SQL
• Location requirements: Hybrid, Barcelona, Spain

About the role

• Principal Scientist ensuring data quality for R&D Data Science at Johnson & Johnson. Leading quality initiatives and collaborating with cross-functional teams in innovative medicine.

Responsibilities

• Develop and maintain a data quality management framework aligned with GxP, FAIR, and enterprise principles.
• Define data quality dimensions (accuracy, completeness, consistency, timeliness, validity, integrity, and lineage) and establish measurable KPIs.
• Partner with Data Governance, Knowledge Management Global Development, Regulatory and Master Data Management (MDM) teams to ensure traceability and alignment of data quality standards across domains.
• Contribute to data stewardship, defining ownership and escalation procedures for quality issues.
• Lead data validation activities across multiple data types — including clinical, real world, omics, manufacturing, and digital health data.
• Identify and enable the use of tools, driving data quality automation and monitoring.
• Design dashboards and reports to convey key metrics and communicate insights to scientists and leadership.
• Collaborate with AI/ML, Global Functions, Real World Evidence, Clinical Data Management, Global Regulatory, J&J Technology, Epidemiology, and the Commercial organization to understand current quality controls and assess the value / need for subsequent controls.
• Act as the liaison between R&D DSDH and J&J Technology, translating quality requirements into technical rules and data validation workflows.
• Ensure data quality processes align (where applicable) to regulatory and industry standards, including FDA 21 CFR Part 11, GCP, GDPR, HIPAA, and ALCOA+ principles.
• Support audit readiness by maintaining robust documentation and evidence of data quality processes.
• Drive adoption of AI-assisted data quality tools and metadata-driven automation to reduce overhead.
• Stay current on emerging data quality trends in the pharmaceutical and healthcare space.
• Mentor junior quality analysts.

Requirements

• 8 – 10+ years of experience in pharma/biotech R&D or commercial functions, with significant exposure to data management or 6+ years of experience in pharma/biotech R&D or commercial functions with advanced degree.
• Experience in master data management, ontology development, and/or knowledge graph application.
• Understanding controlled vocabularies (e.g., SNOMED CT, MedDRA, LOINC).
• Experience in data profiling and validation, including the use of tools and writing in SQL, Python and/or R.
• Experience integrating data across discovery, development, clinical, regulatory, and/or commercial domains.
• Strong understanding of data standardization and harmonization.
• Experience working with / in validated environments.
• Knowledge of FDA and EMA guidelines, especially around GxP, ALCOA+ data integrity principles, and 21 CFR Part 11 compliance.
• Awareness of CDISC, SDTM, ADaM, HDF5 and H5mu standards.
• Strong writing skills for creating / drafting of quality reports, SOPs and general guidelines.

Benefits

• Health insurance
• 401(k) matching
• Paid time off
• Flexible work arrangements
• Professional development opportunities