Associate Director, Clinical Data Engineer (CDE)

Takeda

1d • Remote

About The Position

Clinical Data Engineering (CDE) at Takeda: Key to Takeda’s success the Clinical Data Engineering group is responsible for integrating structured and unstructured data across the various data sources, setup, data transfer/review and support downstream transformation and analysis. CDE also provides support to exploratory and specialty data for the purposes of data modelling, simulation, and analysis. Associate Director, Clinical Data Engineer (CDE) Key to Takeda’s success is the Clinical Data Engineering team, which provides strategic planning, integrating, execution, build and oversight of clinical trial deliverables. Under the guidance of Clinical Data Management, the Clinical Data Engineer provides leadership and guidance at the enterprise level for end-to-end data extraction, transformations and construct of data pipelines that conform to the common data model that ensures data ingestion for all clinical data capture technologies and other related vendor and/or applications (e.g., EDC, IRT, ePRO, eCOA) as well other data models that may be required by end users. Understands and ensures proper data formats for all downstream users for use in the data lake. Facilitates test data transfer to staging instance and confirms accurate DTA specification. Defines processes and develop and maintain code libraries for use by clinical data configuration specialist to build, maintain, and monitor data pipelines for clinical data and the clinical data repository (CDR) alongside processing specialty data for exploratory analysis. Develops and maintains library of reusable mapping and transformation functions to be used across studies. CDE contributes to the successful conduct of Takeda’s clinical trials and to the delivery of high quality in a timely manner, which is eventually used for statistical analysis and submitted to regulatory authorities for the approval of Takeda products. The CDE also monitors end to end performance and KPIs and provides continuous improvement to processes and tools. Further, CDE efforts enable valid secondary use of clinical trial data throughout Takeda research groups to maximize value and achieve company objectives.

Requirements

• Bachelor's degree in computer science, statistics, biostatistics, mathematics, biology or other health related field or equivalent experience that provides the skills and knowledge necessary to perform the job.
• BS with 9+ years’ experience.
• Minimum of 5 years’ experience in data engineering, building data pipelines to manage heterogenous data ingestions or similar in data integration across multiple sources including collected data.
• Experience with Python/R, SQL, NoSQL
• Cloud experience (i.e. AWS, AZURE or GCP)
• Experience with GitLab, GitHub
• Experience deploying data pipelines in the cloud
• Experience with Apache Spark
• Experience setting up and working with data warehouse, data lakes (eg: snowflake, Amazon RedShift etc.,)
• Experience setting up ELT and ETL
• Experience with unstructured data processing and transformation
• Experience developing and maintaining data pipelines for large amounts of data efficiently
• Must understand database concepts.
• Knowledge of XML, JSON, APIs.
• Demonstrated ability to lead junior Data engineers and proven ability to resolve problems independently and collaboratively.
• Must be able to work in a fast-paced environment with demonstrated ability to juggle and prioritize multiple competing tasks and demands.
• Ability to work independently, take initiative and complete tasks to deadlines.
• Strong attention to detail, and organizational skills
• Strong Project leadership and people skills
• Strong understating of end-to-end processes for data collection, extraction and analysis needs by end users
• Strong ability to communicate with cross functional stakeholders
• Strong ability to develop technical specifications based on communication from stakeholders
• Quick learner and comfortable asking questions, learning new technologies and systems

Nice To Haves

• Experience creating custom functions Python/R
• Cloud computing (AWS, Snowflakes, Databricks)
• Ability to visualize large datasets
• R shiny/Python App experience a plus
• Experience developing R shiny and Python apps

Responsibilities

• Ability to manage teams and timelines across multiple functional areas and platforms.
• Mentor and guide other team members
• Advanced knowledge and ability to liaise with outside groups in a matrix environment
• Building required infrastructure for optimal data extraction, transformation and loading of data using cloud technologies like AWS, Azure etc.,
• Develop end to end processes on the enterprise level for use by the clinical data configuration specialist to prepare data extraction and transformations of raw data quickly and efficiently from various sources at the study level
• Manage timelines, deliverables and communications across organization
• Develop and maintain, tools, libraries, and reusable templates of data pipelines and standards for study level consumption by data configuration specialist
• Collaborate with various vendors and cross functional teams to build and align on data transfer specification and ensure a streamlined process of data integration
• Develop organizational knowledge of key data sources, systems and be a valuable resource to people in the company on how to best integrate data to pursue company objectives.
• Provides technical leadership on various aspects of clinical data flow including assisting with the definition, build, and validation of application program interfaces (APIs), data streams, data staging to various systems for data extraction and integration
• Coordinates with data base builders, clinical data configuration specialists and data management (DM) programmers ensuring accuracy of data integration per SOPs
• Provide technical support / consultancy and end-user support, work with Information Technology (IT) in troubleshooting, reporting, and resolving system issues
• Efficiently prepare and process large datasets for various end users for downstream consumption
• Understand end to end requirements for stakeholders and contribute to process and conventions for clinical data ingestion and data transfer agreements
• Adhere to SOPs for computer system validation and all GCP (Good Clinical Practice) regulations
• Performs clinical data engineering tasks according to applicable SOPs (standard operating procedures) and processes.

Benefits

• U.S. based employees may be eligible to participate in 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, and well-being benefits, among others.
• U.S. based employees are also eligible to receive, per calendar year, up to 80 hours of sick time, and new hires are eligible to accrue up to 120 hours of paid vacation.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees