Clinical Data Standards and Master Data Digital Solution Lead

About the role

Roche is looking for a Digital Solution Lead in its PD Data Sciences area in Madrid. You will lead the strategy, operating model and delivery governance for Clinical Data Standards, Master Data and the supporting technology ecosystem, including the in-house Global Clinical Data Standards Repository (GDSR) and Lynx. You work with Clinical Data Management, Biostatistics, Study Teams, Roche Data Technologies and Enterprise Informatics to define clinical data once, govern it consistently and deliver it reliably.

Key responsibilities

• Lead the domain vision for clinical data standards, master data and supporting technologies, acting as a subject matter expert in CDISC, master/reference data and semantic modelling
• Resolve complex issues on standards adoption, metadata definition, master data stewardship, technology integration and downstream consumption, and drive root cause analysis
• Build partnerships across PD Data Sciences, Clinical Data Management, Biostatistics, Regulatory, Architecture, Informatics and external partners, and escalate risks and blockers
• Define the roadmap for standards and master data capabilities, including GDSR and Lynx, and connect the domain strategy to enterprise data and AI ambitions
• Shape requirements for in-house solutions, support the use of Roche delivery frameworks such as SPEED, and promote automation, traceability and quality engineering

Required profile

• Extensive experience leading cross-functional initiatives in clinical data, data standards, metadata, master data or informatics in pharma, biotech or a regulated environment
• Proven experience defining and embedding CDISC standards (CDASH, SDTM, ADaM, Define-XML, controlled terminology) into business processes and technology
• Experience overseeing delivery of critical data or metadata platforms, including vendor governance, release planning and service health monitoring
• Ability to set KPI dashboards and structured tracking for milestones, incidents and defects
• Stakeholder management and communication skills; experience in clinical development, regulatory data flows or AI-ready data foundations is highly desirable

Required skills

• CDISC standards, controlled terminology, metadata management and traceability
• Semantic modelling, canonical data models, ontologies and knowledge representation
• Master data and reference data management, including stewardship, quality controls, versioning and lineage
• Data integration patterns, APIs, metadata repositories, cloud data platforms and graph/semantic technologies
• Familiarity with quality engineering, automated testing, audit trails, change control and GxP compliance