veeva jobs in San Diego

Senior Director responsible for designing, building, and scaling enterprise technology platforms serving Commercial and Global Medical Affairs at a biotech company. Oversees a portfolio including Veeva, Salesforce CRM, PromoMats, MedComms, master data, field enablement, market access, patient services, and analytics integrations.…See more Leads cross-functional teams, vendors, and systems integrators to simplify the technology footprint, embed compliance and security, drive process improvement, and realize benefits from new capabilities. Requires 12+ years of progressive IT/business technology experience, with 8+ years in biotech/pharma and 5+ years supporting Commercial and Medical Affairs functions.

As Associate Director of Customer Engagement Platforms & Data, you will lead product management, solution architecture, and delivery for commercial and medical affairs customer engagement capabilities—including Veeva and Salesforce CRM, marketing automation, and digital engagement platforms. You will translate business and data strategies into product plans and technical requirements, partner across Commercial Systems & Analytics and Enterprise Data & Intelligence to align roadmaps and governance, and provide hands-on delivery leadership from discovery through deployment and continuous improvement.…See more The role requires balancing product ownership with technical accountability for architecture, security, scalability, compliance, and data governance in a shared operating model with cross-functional teams.

Principal Engineer leading the design, build, and operation of an enterprise data platform serving 50+ source systems across R&D, Commercial, Manufacturing, and other business functions. The role combines hands-on data engineering (PySpark, T-SQL, Python, Data Factory, medallion architecture) with technical leadership of data engineers, vendor management, platform standards enforcement, and cross-functional stakeholder partnership.…See more Responsibilities span CI/CD pipeline design, data quality and reliability instrumentation, semantic layer development, data governance implementation, and delivery of new source-system integrations at scale.