The Clinical Data Engineer role serves the purpose of fostering innovation and operational efficiency through the facilitation of data-driven decision-making processes, expediting drug discovery initiatives, and bolstering regulatory compliance efforts. This role involves designing and implementing customized data pipeline architecture solutions tailored to the complexities of life sciences research and development. It also includes supervising the integration and management of various clinical data and data sources, such as clinical trials data, operational data, lab data, wearables data, and real-world evidence.

Through close collaboration with study leads, research scientists, statisticians, clinicians, regulatory experts, and DigitalX professionals, this role establishes and upholds robust data architecture frameworks that align harmoniously with business objectives, regulatory mandates, and industry standards. Expertise in Data Engineering, Data Modeling, and adeptly managing governance processes is essential for maintaining the integrity, security, and accessibility of data assets. This role holds a strategic position in advancing the life sciences company's mission by using data to drive scientific progress, improve patient outcomes, and efficiently and securely introduce ground-breaking therapies to the market.

Responsibilities and Accountabilities:

·       ​​​Responsible for data operations on AWS architecture. Activities include creating and monitoring the data load ETL processes, ensuring data quality, automation of the loads and continuous improvement.  

·       ​Collaborate with internal and external teams for data curation, cataloging and metadata management.

·       Strong knowledge of RWD assets including data sources like IQVIA, SYMPHONY and various other OMICS sources.

·       Ensure the operations schedule and knowledge base are maintained and communicated promptly to the end users.  

·       ​Assist in enforcing data governance and information management policies, SOPs, and standards to manage patient data in a secure and compliant manner. 

·       Strong proficiency in Python and Django framework including experience with web technologies such as HTML, CSS, JavaScript, and AJAX.

·       Understanding of RESTful APIs and web services integration. Additionally, Familiarity with deployment tools such as Docker, Heroku, AWS, or Azure.

·       Knowledge of database management systems, particularly PostgreSQL or MySQL.

·       Experience with unit testing and test-driven development (TDD).

·       Experience with JavaScript frameworks like React, Angular, or Vue.js and other modern API technologies.

·       ​​Identify areas for improvement with current analytics tool sets and propose future state to support DigitalX use cases, analytics best practices, and regulations. 

·       ​Improving the delivery of large complex projects by implementing standard processes, tools, and templates that will be used consistently across Digital.

·       Participate in several concurrent projects in Advanced Analytics Solutions for the various functions across Astellas in a fast-paced environment.

·       Ensure the RWD Analytics environments are running at an optimal state and quickly resolve any technical issues. 

·       Participate in process improvements initiatives involving business areas. 

·       Collaborate with Advanced Analytics Solution teams to identify required technology architecture needs to design and implement a solution delivering near-term impact and aligned with long term strategies.

·       Implement security requirements, metadata standards, data quality and testing procedures for the data lake/warehouse consistent with analytic and RWD best practices.