Principal Data Engineer, Biometrics

Who We Are: Neurocrine Biosciences is a leading biopharmaceutical company with a simple purpose: to relieve suffering for people with great needs. We are dedicated to discovering, developing and commercializing life-changing treatments for patients with under-addressed neurological, psychiatric, endocrine and immunological disorders. The company's diverse portfolio includes FDA-approved treatments for tardive dyskinesia, chorea associated with Huntington's disease, classic congenital adrenal hyperplasia, hyperphagia in Prader-Willi syndrome, 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 more than 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 , Facebook and YouTube . ( *in collaboration with AbbVie ) About the Role: This role will serve as an experienced data engineering professional responsible for designing, developing, implementing, and maintaining complex data engineering solutions that support Neurocrine's Clinical programs, including Clinical Data Management, Statistical Programming, and Biostatistics functions. This role sits on the regulated data path that runs from clinical data collection through analysis datasets, and ultimately submission to regulatory agencies. The ideal candidate brings fluency in CDISC standards (CDASH, SDTM, ADaM, and controlled terminology) and other industry-standard clinical data models, along with the software engineering discipline needed to build, validate, and maintain tools in a GxP environment. Work directly targets faster study database builds, higher data quality, more efficient dataset and output generation, and the ability of Biometrics to scale as Neurocrine's pipeline grows. This role analyzes and resolves complex technical challenges, partnering across functions to evaluate underlying needs, recommend appropriate solutions, and implement scalable improvements. The position requires sound judgment and the ability to translate business requirements into effective, sustainable data engineering solutions. The role contributes to the development and implementation of technical standards and best practices, supports the adoption of solutions, and ensures appropriate documentation, training, and ongoing support to sustain long-term effectiveness. _ Your Contributions (include, but are not limited to): Collaborate cross-functionally with clinical Data Management, Statistical Programming, and Biostatistics to evaluate complex workflows, identify opportunities for improvement, define solution requirements, and identify measurable success criteria for data engineering initiatives Translate Biometrics processes into maintained, production-grade data products with clear ownership, versioning, and support Design, build, and maintain pipelines that move clinical data from collection systems (EDC, eCOA, central labs, and other vendors) into standards-compliant, analysis-ready datasets Develop automation across the CDISC data flow, including CDASH-aligned collection, SDTM dataset generation, and support for ADaM and TFL production, maintaining traceability end to end Build data quality and review tools, such as automated checks and outlier detection, that shift review from manual inspection to exception-based workflows Develop tools that accelerate study start-up, including protocol-to-SoA-to-CRF review, standards-based EDC database build, and protocol-to-SAP and SAP-to-TFL shell automation Support Medical Writing and Biostatistics with automated, standards-driven document outputs Assist in defining vendor data transfer specifications and implementing direct vendor-to-EDC and vendor-to-lake transfers in partnership with integration and platform colleagues Apply established SDLC and computer system validation practices for GxP-related systems, including requirements, risk assessment, testing, traceability, change control, and release documentation, to ensure compliant, inspection-ready solutions Support successful implementation and adoption of delivered tools through user training, documentation, and ongoing feedback, and measure impact through usage, time saved, and quality improvements Collaborate with platform and AI engineering colleagues so Biometrics data products align with the enterprise data lake, governance model, and downstream analytics Serve as a technical resource and advisor to Biometrics and Clinical stakeholders, providing technical recommendations, evaluating emerging technologies and vendor solutions, and recommending solutions that address business and technical requirements Other job-related duties as assigned Requirements: Bachelor's Degree in Computer Science, Engineering, Bioinformatics, Statistics, or a related field AND 6+ years in data engineering, statistical programming, or clinical data management, including work in a regulated clinical environment OR Master's Degree in Computer Science, Engineering, Bioinformatics, Statistics, or a related field AND 4+ years as noted above Advanced knowledge in CDISC standards, including CDASH, SDTM, ADaM, controlled terminology, and define.xml, with an understanding of their application across clinical data collection, analysis, and regulatory submission Demonstrated experience designing, developing, and maintaining complex, production-grade data engineering solutions supporting clinical data management, statistical programming, or biostatistics Strong proficiency in Python, SQL, database design, and data modeling, with working knowledge of SAS and/or R Advanced knowledge of software engineering best practices, including Git/GitHub, CI/CD, automated testing, and maintainable code development Experience with clinical data structures and integration ac