Sr. Clinical Data Engineer - San Diego based

Role Summary

Sr. Clinical Data Engineer responsible for designing, implementing, and maintaining data infrastructure and solutions to support clinical trials and development programs. Collaborates with Clinical Operations & Development, Biometrics, and IT teams to develop data pipelines, integrate clinical systems, and deliver analytical solutions enabling data-driven decision-making throughout the trial lifecycle. Builds scalable data models and transformation workflows to support analytics and machine learning initiatives.

Responsibilities

• Collaborate with team members to develop and maintain data solutions for clinical stakeholders
• Empower scientists, researchers, and management with efficient access to high-quality data insights
• Maintain and create end-to-end solutions, including data ingression, modeling, and visualization
• Design and implement data models optimized for analytical querying, reporting, and ML workflows
• Solve challenges related to multi-model data sources, harmonization, and normalization
• Provide technical leadership in evaluating and implementing new tools and technologies
• Assist in management and selection of optimal data transfer approaches among different vendors
• Develop and deploy end-user facing solutions to production using SDLC best practices
• Create and maintain documentation to support development work, definitions, and business rules
• Adhere to regulatory guidelines (e.g., GxP, HIPAA, GDPR) and security policies in handling data
• Act as a data and analytical consultant to stakeholders on data utility issues
• Support the clinical team with planning and execution of clinical studies

Qualifications

• Required: Bachelor's Degree in Computer Science, Engineering, Bioinformatics, or related field and 4+ years in an analytical capacity with development/maintenance of reports
• OR: Master's Degree in Computer Science, Engineering, Bioinformatics, or related field and 2+ years as noted above
• Demonstrated passion for practically solving complex problems with technology
• Excellent communication skills and ability to work with cross-functional teams
• Ability to manage multiple priorities to meet deadlines
• Prior bio/pharma experience is highly preferred, but not required
• Demonstrated experience implementing production data models and analytical solutions
• Strong programming skills in Python and other modern languages
• Strong expertise in database design, SQL optimization, and data modeling patterns
• Strong expertise with cloud infrastructure and computing platforms; AWS experience preferred
• Advanced knowledge of clean code principles, testing methodologies, GitHub, and CI/CD tools
• Advanced knowledge in data analysis, exploration, and visualization tools
• Experience with statistical concepts and methods (descriptives, probability, hypothesis testing)
• Familiarity with clinical data standards (CDISC, SDTM, ADaM) and GCP regulatory guidelines

Education

• As listed in Qualifications