Sr. Data Engineer - Analytical Development
About The Position
The AD Technology Development and Implementation team at Takeda is in search of a data Sr. Staff Engineer to contribute to the design, implementation, and deployment of event driven ETL pipelines with AWS to ingest and process structured and unstructured laboratory records. Our team strives to analyze laboratory method characterization data by using modern data platforms, standard methodologies, and thoughtful predictive modeling. In this role, a typical day might include the following: Develop and maintain Analytical Development (AD) digital transformation road map. Deliver established vision, roadmap, projects, and timeline to support the digital transformation of analytical laboratory results. Support large database activities, design and maintain open-source code extraction algorithms Assume technical ownership on digital transformation projects, which include but are not limited to data analytics and predictive modeling, dashboards using Spotfire, Tableau, Power BI, and open-sourced coding (i.e., R and Python) Develop and maintain core software engineering infrastructure within data platform engineering & operations, including data wrangling, data logging, performance benchmarking, and multi-platform integration Contribute to multiple software engineering efforts, including data engineering/analytic pipelines, and data platforms Coordinate with other development teams to promote collaborative data management efforts, interoperability, and shared infrastructure Monitor data capture systems to identify inefficiencies and remove bottlenecks Support internal & external R&D projects, working with domain experts to mature POCs into production-quality tools
Requirements
- B.S. degree in computer science, software engineering, or a related field with 11+ years of relevant industry experience, M.S. and 9+ years of relevant industry experience, or PhD and 3+ years of relevant industry experience.
- Minimum of 8 years of combined experience in the analytical environment utilizing SQL, Cloud environments, AWS, Python, Dev-Ops and R Studio.
- Experience with ETL pipelines, data pre-processing, and statistical concepts.
- Ability to work in multiple languages (Python, R, Scala, C/C++, SQL).
- Strong understanding of analytical software (Spotfire, Minitab, MATLAB).
- Demonstrated experience contributing to and maintaining multi-contributor software projects (open or closed source), pipelines, and/or enterprise systems.
- Ability to collaborate with other coworkers and work with multi-functional teams of developers, engineers, and scientists.
Nice To Haves
- Exposure to cloud computing environments and technologies in the data & analytics engineering domain (Spark, Databricks, data lakes, data QA tools, ML tools) are a plus but not required.
- Previous direct involvement in technology implementations for use in biologics, pharmaceuticals or devices, either in manufacturing operations or support function is highly desirable.
- Interacts with vendors of applications, integrators and consultants during front end studies, design workshops and system implementation.
Responsibilities
- Develop and maintain Analytical Development (AD) digital transformation road map.
- Deliver established vision, roadmap, projects, and timeline to support the digital transformation of analytical laboratory results.
- Support large database activities, design and maintain open-source code extraction algorithms.
- Assume technical ownership on digital transformation projects, which include but are not limited to data analytics and predictive modeling, dashboards using Spotfire, Tableau, Power BI, and open-sourced coding (i.e., R and Python).
- Develop and maintain core software engineering infrastructure within data platform engineering & operations, including data wrangling, data logging, performance benchmarking, and multi-platform integration.
- Contribute to multiple software engineering efforts, including data engineering/analytic pipelines, and data platforms.
- Coordinate with other development teams to promote collaborative data management efforts, interoperability, and shared infrastructure.
- Monitor data capture systems to identify inefficiencies and remove bottlenecks.
- Support internal & external R&D projects, working with domain experts to mature POCs into production-quality tools.
Benefits
- medical, dental, vision insurance
- a 401(k) plan and company match
- short-term and long-term disability coverage
- basic life insurance
- a tuition reimbursement program
- paid volunteer time off
- company holidays
- well-being benefits
- up to 80 hours of sick time per calendar year
- up to 120 hours of paid vacation for new hires
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What This Job Offers
Job Type
Full-time
Career Level
Senior
