Principal, Clinical Data Management Lead

Main Responsibilities and Accountabilities

• Leads and develops a team of Clinical Data Validators, providing direction on clinical data standards, validation, and oversight activities across in-house, hybrid, and vendor-supported studies.
• Establishes and drives clinical data governance frameworks, including review and validation processes for eCRF builds, SDTM datasets, specifications, and vendor deliverables, ensuring compliance with internal standards, regulatory requirements, and industry best practices.
• Oversees the development, implementation, and continuous improvement of clinical data standards (e.g., CDASH, SDTM) and associated validation check libraries to enable consistent, scalable, and high-quality data across studies.
• Provides strategic oversight of data integration processes, including external data flows and system interfaces, ensuring accurate, efficient, and compliant data ingestion into downstream platforms such as the Clinical Data Warehouse.
• Ensures submission readiness of clinical data by establishing robust quality control frameworks and validation processes aligned with regulatory expectations (e.g., SDTM, ADaM, define.xml).
• Develops, maintains, and governs departmental and cross-functional SOPs, standards, and QMS documentation related to clinical data oversight, standards, and programming.
• Drives cross-functional alignment by partnering with Biostatistics, Data Management, Standards, and external partners to ensure consistent understanding and application of clinical data standards and quality expectations; provides guidance, knowledge sharing, and targeted training to support effective implementation across studies.
• Provides oversight and guidance on data storage, archival, and retrieval strategies to support regulatory submissions, pooled analyses, and reuse of legacy data in collaboration with Biostatistics and other stakeholders.
• Oversees programming and validation support to ensure availability of high-quality, analysis-ready datasets, while promoting automation, efficiency, and innovation through the use of SAS and emerging technologies (e.g., Python, AI-driven solutions).

Job Qualifications and Experience Requirements

• Education: Degree (BSc/MSc/Diploma) in Computer Science, Mathematics/Statistics, or related area with relevant experience. Other degrees and certifications considered, if commensurate with related data management/statistical programming experience.
• Experience: At least 7 years of relevant experience with EDC and/or Clinical Data Warehouse platforms (e.g., Medidata Rave, Veeva Vault), with a solid understanding of data flows, integrations, and database structures within the CRO/pharmaceutical environment.
• Significant experience with demonstrated leadership or oversight responsibilities and a strong understanding of the end-to-end clinical data lifecycle, including data collection, validation, standards implementation, and regulatory submission requirements.
• Proven expertise in CDISC standards (CDASH, SDTM, ADaM) and their practical application across studies, including review and oversight of datasets, specifications, and mappings.
• Proficiency in SAS programming, with working knowledge of Python, R, or similar languages preferred to support automation and advanced data review.
• Demonstrated experience in establishing or applying data quality frameworks, validation processes, and governance models in a clinical data environment.
• Proven ability to manage priorities, timelines, and team deliverables in a fast-paced environment, while driving continuous improvement and operational excellence.
• Experience with CROs (either managing a CRO, or having worked in a CRO).