Associate Director, Clinical Data Engineer; CDE

Job Description

Associate Director, Clinical Data Engineer (CDE) – Key to Takeda’s success the Clinical Data Engineering group is responsible for integrating structured and unstructured data across the various data sources, setting up data transfer, reviewing and supporting downstream transformation and analysis. CDE also provides support to exploratory and specialty data for the purposes of data modelling, simulation, and analysis.

• 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.

• 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, No
  
  SQL
• Cloud experience (i.e. AWS, AZURE or GCP)
• Experience with Git Lab, Git Hub
• Experience deploying data pipelines in the cloud
• Experience with Apache Spark
• Experience setting up and working with data warehouse, data lakes (eg: snowflake, Amazon Red Shift 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 understanding of end-to-end processes for data collection, extraction…