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Clinical Data Engineer

2 months ago


Markham, Ontario, Canada Astellas Full time
About the Role

We are seeking a highly skilled Clinical Data Engineer to join our team at Astellas. As a Clinical Data Engineer, you will play a critical role in fostering innovation and operational efficiency through the facilitation of data-driven decision-making processes.

Key Responsibilities
  • Design and Implement Data Streaming Architecture: Develop comprehensive data streaming architecture strategies tailored to the needs of Clinical and Operational data management.
  • Develop and Maintain ETL Processes: Design, develop, and maintain ETL (Extract, Transform, Load) processes to efficiently move clinical data from various sources to target systems.
  • Develop Data Load Strategies: Develop and implement data load strategies to ensure design integrity and flexibility.
  • Develop Data Transformation Logic: Develop and implement data transformation logic to clean, standardize, and enrich raw clinical data.
  • Optimize Data Workflows: Optimize data workflows and performance through automation, parallel processing, and data partitioning techniques.
  • Design Scalable Data Pipeline Architectures: Design scalable data pipeline architectures to handle large volumes of clinical data.
  • Develop APIs and Interfaces: Develop APIs, interfaces, and middleware solutions for seamless communication between clinical software systems and databases.
  • Ensure Data Compatibility and Compliance: Ensure data compatibility and compliance with industry standards such as HL7, FHIR, ICH M11, and others.
  • Implement Security Controls: Implement security controls, encryption mechanisms, redaction logic, and access management policies to protect sensitive data from unauthorized access, breaches, and cyber threats.
  • Monitor Compliance and Performance: Continuously monitor ETL job performance and make necessary adjustments to improve speed and reliability.
  • Document Data Flow Designs: Document data flow designs, technical specifications, and operational procedures to facilitate knowledge transfer and support ongoing maintenance and enhancements.
  • Identify and Address Potential Bottlenecks: Proactively identify and address potential bottlenecks and challenges in data processing workflows.
  • Collaborate with Cross-Functional Teams: Work closely with cross-functional teams including data managers, clinical leads, statisticians, statistical programmers, researchers, DigitalX members, and regulatory experts to understand requirements and priorities for clinical data management and analysis.
  • Participate in Data Governance Initiatives: Participate in data governance initiatives to standardize data practices and ensure compliance with organizational policies.
  • Stay Up-to-Date with Emerging Technologies: Stay abreast of emerging technologies, trends, and best practices in clinical data management, architecture, and engineering.