Associate Director, Clinical Data Engineer (CDE)
Scorpion Therapeutics, New Bremen, Ohio, United States
Role Summary
Associate Director, Clinical Data Engineer (CDE) at Takeda. The Clinical Data Engineering group integrates structured and unstructured data across data sources, supports data transfer, transformation, and downstream analysis for clinical trials, and enables data modelling, simulation, and exploratory analyses. The CDE leads end-to-end data extraction and pipelines aligned to a common data model, ensuring ingestion for clinical data capture technologies and related applications for downstream analytics. Location: Massachusetts - Virtual. 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 Qualifications
Experience: BS with 9+ years of experience; minimum 5 years in data engineering, building data pipelines to manage heterogeneous data ingestions or similar in data integration across multiple sources; experience with Python/R, SQL, NoSQL; cloud experience (AWS, Azure or GCP); experience deploying data pipelines in the cloud; experience with Apache Spark; experience setting up data warehouses and data lakes (e.g., Snowflake, Amazon RedShift); experience ELT and ETL; experience with unstructured data processing; experience leading junior data engineers; ability to work in a fast-paced environment and juggle multiple tasks; ability to work independently and meet deadlines License/Certifications: Preferred to have AWS or R or Python certification Education
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 Skills
Strong attention to detail and organizational skills Strong project leadership and people skills Strong understanding 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 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
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Associate Director, Clinical Data Engineer (CDE) at Takeda. The Clinical Data Engineering group integrates structured and unstructured data across data sources, supports data transfer, transformation, and downstream analysis for clinical trials, and enables data modelling, simulation, and exploratory analyses. The CDE leads end-to-end data extraction and pipelines aligned to a common data model, ensuring ingestion for clinical data capture technologies and related applications for downstream analytics. Location: Massachusetts - Virtual. 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 Qualifications
Experience: BS with 9+ years of experience; minimum 5 years in data engineering, building data pipelines to manage heterogeneous data ingestions or similar in data integration across multiple sources; experience with Python/R, SQL, NoSQL; cloud experience (AWS, Azure or GCP); experience deploying data pipelines in the cloud; experience with Apache Spark; experience setting up data warehouses and data lakes (e.g., Snowflake, Amazon RedShift); experience ELT and ETL; experience with unstructured data processing; experience leading junior data engineers; ability to work in a fast-paced environment and juggle multiple tasks; ability to work independently and meet deadlines License/Certifications: Preferred to have AWS or R or Python certification Education
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 Skills
Strong attention to detail and organizational skills Strong project leadership and people skills Strong understanding 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 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
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