Job
Description
Data Quality System Testing Expert Location: Remote Objective: The Data Quality System Testing Expert is responsible for leading and executing user acceptance testing (UAT) and validation of clinical study builds in EDC systems (e.g., Veeva CDMS, Medidata Rave). The role ensures study database quality and compliance with technical specifications and regulatory standards, supporting cross-functional teams in delivering accurate, reliable data for clinical trials. Key Responsibilities: Testing Execution & Documentation Create and execute test plans, UAT scripts, and summary reports in Excel or ALM. Develop and execute standardized test cases for EDC components, data listings, and system integrations. Document and analyze testing outcomes, identifying and reporting defects. System & Process Expertise Validate EDC system builds and confirm compliance with established standards. Lead UAT activities for study and library configurations, including Agile-based workflows and system integrations. Collaboration & Communication Interface with clinical teams, vendors, and internal stakeholders to ensure integration accuracy and timely resolution of testing issues. Provide training and support for UAT processes and best practices. Innovation & Improvement Participate in process improvement initiatives and automation of testing procedures. Recommend tools and practices for enhancing testing efficiency and data quality. Qualifications & Experience: Bachelor’s or Master’s degree in Life Sciences, Computer Science, Engineering, or related field. ~10 years in a pharmaceutical or CRO environment, focusing on clinical systems testing and data management. Extensive experience with EDC systems (Veeva CDMS, Rave), clinical research tools (eCOA, IRT, RTSM), and data flow infrastructure. Familiar with testing tools (ALM, UFT, Tosca, Qtest) and regulatory standards. Proficiency in Agile methodology and clinical study lifecycle understanding. Strong documentation, communication, and problem-solving skills. Key Competencies: Deep knowledge of clinical data systems and study design. Proven leadership in UAT execution and cross-functional project coordination. Adaptability to complex, global environments. Demonstrated innovation and change management abilities.
