Sr. Data Engineer - Analytical Development

Overview In this role, you will lead the design, implementation, and deployment of event-driven ETL pipelines on AWS to ingest and process structured and unstructured lab records. You’ll drive analytical development digital transformation and partner with cross-functional teams to advance data platforms, predictive modeling, and dashboards. You’ll own core software engineering infrastructure for data platforms and guide multiple projects from POC to production. This is a hands-on senior role at the intersection of data engineering, analytics, and biopharma. Join a hybrid-friendly team shaping the future of analytical development at Takeda. Compensation / Benefitsbase salary rangemedical, dental, vision insurance401(k) plan and company matchtuition reimbursementpaid volunteer time offwell-being benefits ResponsibilitiesDevelop and maintain Analytical Development (AD) digital transformation road map and deliver the vision, roadmap, projects, and timelineOwn digital transformation projects including data analytics, predictive modeling, and dashboards (Spotfire, Tableau, Power BI) and open-source coding (R, Python)Develop and maintain core software engineering infrastructure within data platform engineering & operations (data wrangling, logging, benchmarking, multi-platform integration)Contribute to data engineering/analytic pipelines and data platforms across multiple software initiativesCoordinate with other development teams to promote interoperable data management and shared infrastructureMonitor data capture systems to identify inefficiencies and bottlenecksSupport internal & external R&D projects and mature POCs into production-quality toolsPromote collaboration with vendors, integrators, and cross-functional teamsEngage with multi-functional teams of developers, engineers, and scientists Key requirementsB.S. in computer science, software engineering, or related field with 11+ years, M.S. with 9+ years, or PhD with 3+ years of relevant experienceMinimum 8 years of experience in analytical environment using SQL, Cloud environments, AWS, Python, Dev-Ops, and R StudioExperience with ETL pipelines, data pre-processing, and statistical concepts; proficient in Python, R, Scala, C/C++, SQLExposure to cloud computing technologies in data & analytics (Spark, Databricks, data lakes, data QA tools, ML tools) is a plusStrong knowledge of analytical software (Spotfire, Minitab, MATLAB) and experience with multi-contributor software projectsPrior involvement in technology implementations in biologics/pharmaceuticals/devicesAbility to collaborate with vendors and cross-functional teams; hybrid work modelcollaborationcross-functional teamworkcommunicationSQLAWSPython