Teams at BASE life science

Build and maintain automated data ingestion and transformation pipelines using Azure Databricks, Azure Data Factory, SQL, Python, and PySpark. Ensure data quality, lineage, monitoring, auditing, error handling, and reliable downstream analytics. Collaborate with analysts, privacy officers, quality teams, and pharmaceutical domain experts on data architecture, testing, integration, and business intelligence projects.

Translate life sciences clients’ business needs into user stories and technology requirements, and participate in IT implementation projects from initiation through completion. Analyze pharma commercial processes, support data and analytics initiatives, facilitate workshops, document requirements, align stakeholders, and help clients address analytics challenges. The role requires collaboration with technical and business teams and may involve implementing cloud and commercial life sciences solutions.

Leads complex technical projects and programs for life sciences clients, including implementation, migration, software development, and data initiatives. Responsibilities include planning scope, timelines, budgets, risks, and resources; leading cross-functional teams; managing client communications and escalations; translating business requirements into technical plans; supporting proposals and business development; and improving internal project management methodologies.