Clinical SAS Programmer

Purpose:

The Clinical Data Systems Designer I supports the delivery of clinical trial data systems, external vendor data acquisition, and fit-for-purpose datasets for reporting, analysis, and regulatory submissions. The role brings together people, processes, and technology to generate business value from clinical trial data. The position ensures that study protocol requirements are appropriately reflected in clinical system designs, external vendor data-acquisition requirements, system integrations, data aggregation, data transformation, and data quality controls. The role also supports the consistent use of common clinical data standards across studies, programs, and therapeutic areas.

Responsibilities:

• Leads external vendor data acquisition for multiple concurrent studies throughout the study lifecycle, from requirements definition and specification development through data delivery, issue resolution, reconciliation, and study closeout.
• Ensures that study protocol requirements are accurately reflected in clinical system designs, external data-acquisition requirements, and applicable clinical data standards, including CDISC, CDASH, and SDTM.
• Collaborates extensively with Data and Statistical Sciences, clinical study teams, data management, programming, technology teams, external vendors, and other cross-functional partners to achieve study and program objectives.
• Aggregates clinical trial data from multiple internal and external sources into centralized clinical data warehouses; supports data transformation, multisource reconciliation, quality controls, and delivery of SDTM and reporting-ready datasets.
• Accountable for the timely design and delivery of clinical systems, system integrations, and required system changes, including EDC and IRT, while using project-management tools to track study progress and plan work.
• Coordinates upstream and downstream dependencies, anticipates risks to timelines or data quality, and develops practical options and solutions to maintain delivery across assigned studies.
• Serves as a clinical data systems and technology point of contact, working with data and statistical colleagues and external vendors to troubleshoot data-acquisition, integration, reconciliation, and process-flow issues.
• Promotes therapeutic-area and program-level consistency in clinical system design, external vendor data acquisition, data standards, and data-processing approaches.
• Acts as a clinical data systems subject matter expert during regulatory inspections and internal quality audits and ensures adherence to applicable regulations, Google Cloud Platform, ICH guidelines, SOPs, and functional quality standards.
• Coaches and mentors Data Science Associates and contributes to cross-functional innovation, standardization, and continuous process-improvement initiatives.

Qualifications:

• Bachelor's degree in business, management information systems, computer science, life sciences, or an equivalent field; master's degree preferred.
• At least 3 years of clinical technology experience involving systems such as EDC, IRT, or ePRO; or at least 5 years of experience in a similar technical or clinical development role.
• Demonstrated knowledge of clinical research, the clinical trial process, and the full study lifecycle.
• Working knowledge of CDISC standards, including CDASH and SDTM.
• Demonstrated SAS and/or SQL programming skills and knowledge of database concepts.
• Experience with clinical system design, integrations, clinical data warehouses, multisource data aggregation, data transformation, data reconciliation, and standardized or reporting-ready clinical datasets preferred.
• Experience leading external vendor data acquisition across multiple concurrent studies throughout the study lifecycle, including the development of third-party data acquisition specifications.
• Demonstrated analytical, troubleshooting, and problem-solving skills.
• Demonstrated effective written and verbal communication skills and the ability to influence others without direct authority.
• Demonstrated ability to collaborate extensively across functions, influence without direct authority, manage upstream and downstream dependencies, and support process improvement and technology innovation initiatives.

Key Stakeholders:

• Data and Statistical Sciences teams
• Clinical study and program teams
• Clinical technology and systems teams
• Data management and programming functions
• Cross-functional partners supporting clinical development