Clinical Data Programmer

The Clinical Data Programmer is responsible for designing, programming, testing, and supporting electronic clinical data collection and data management systems for clinical trials. The role supports eCOA, eDC, eSource, and Direct Data Capture implementations, including electronic CRF design, data mappings, database structures, validations, and clinical data workflows.

• Programming experience with HTML, CSS, JAVASCRIPT, Node.js, JSON, SpEL
• Experience with relational and non-relational database technologies utilizing SQL, Data Functions and Procedures. (e.g., MongoDB)
• Technical proficiency with HTML, Data Mapping, understanding of database structures, etc.
• Experience handling GITLAB utilities
• Quick learner to new trends in technology
• Excellent leadership, communication (written and oral) and interpersonal skills
• Demonstrated leadership in professional setting
• Demonstrated teamwork and collaboration in a professional setting
• Bachelor's degree in one of the following fields is typically required:
• Computer Science
• Information Technology
• Clinical Research
• Life Sciences
• Bioinformatics
• Health Informatics
• Gather and influence eCOA design specifications to enable successful trial implementation
• Program and test data collection systems and associated data repository mappings for a trial or set of trials within a program using data standards library components
• Ensure data collection systems and data warehouse mappings are delivered accurately, efficiently and in alignment with study objectives
• Partner with Clinical Build Programmer to ensure complete data build for trial data collection needs
• Provide insights into study level deliverables (i.e., Data Management Plan, Project Plan, database, and observed datasets)
• Support submission, inspection and regulatory response activities
• Lead cross Business Unit/Therapeutic Area projects or programs with high complexity
• Hands-on experience as programmer in eCOA (electronic Clinical Outcome Assessment) or eDC (electronic data capture), eSource or Direct Data Capture implementation
• Design of electronic CRF screens to capture Clinical data and build on required validations
• Understanding of Clinical Protocol and interpretation of the Clinical terminologies to create or design specifications
• Familiarity with Clinical data tools, technologies, workflow for collecting patient data, testing and validation of system
• Analyse the impact and implement post production changes the Study design
• Data analytics and visualizations
• Articulating the flow of data (structure and format) from patient to analysis and apply this knowledge to data solutions
• Deciding the technology platform (system/database) for data acquisition and aggregation