Sr. Clinical Data Engineer - San Diego

Who We Are: At Neurocrine Biosciences, we pride ourselves on having a strong, inclusive, and positive culture based on our shared purpose and values. We know what it takes to be great, and we are as passionate about our people as we are about our purpose - to relieve suffering for people with great needs. What We Do: Neurocrine Biosciences is a leading neuroscience-focused, biopharmaceutical company with a simple purpose: to relieve suffering for people with great needs. We are dedicated to discovering and developing life-changing treatments for patients with under-addressed neurological, neuroendocrine and neuropsychiatric disorders. The company's diverse portfolio includes FDA-approved treatments for tardive dyskinesia, chorea associated with Huntington's disease, classic congenital adrenal hyperplasia, endometriosis* and uterine fibroids,* as well as a robust pipeline including multiple compounds in mid- to late-phase clinical development across our core therapeutic areas. For three decades, we have applied our unique insight into neuroscience and the interconnections between brain and body systems to treat complex conditions. We relentlessly pursue medicines to ease the burden of debilitating diseases and disorders because you deserve brave science. For more information, visit neurocrine.com, and follow the company on LinkedIn, X and Facebook. (*in collaboration with AbbVie) About the Role: Plays a crucial role in designing, implementing, and maintaining data infrastructure and solutions that support Neurocrine's clinical trials and development programs. This position will work closely with Clinical Operations & Development, Biometrics, and IT teams to develop and optimize data pipelines, integrate various clinical systems, and deliver analytical solutions that enable data-driven decision-making throughout the clinical trial lifecycle. The role requires a strong technical background combined with an understanding of clinical research processes and data requirements, with particular emphasis on building scalable data models and transformation workflows that support advanced analytics and machine learning initiatives. _ Your Contributions: 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 Other job-related duties as assigned Requirements: Bachelor's Degree in Computer Science, Engineering, Bioinformatics, or a related field and 4+ years in an analytical capacity in conjunction with the development/maintenance of a reports OR Master's Degree in Computer Science, Engineering, Bioinformatics, or a 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 programming languages Strong expertise in database design, SQL optimization, and data modeling patterns Strong expertise with cloud infrastructure and computing platforms, AWS ecosystem preferred Advanced knowledge with 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

Salary : $101,000 - $147,000