Clinical Data Engineer (ETL)
Do you want to be part of an inclusive team that works to develop innovative therapies for patients? Every day, we are driven to develop and deliver innovative and effective new medicines to patients and physicians. If you want to be part of this exciting work, you belong at Astellas!
Astellas Pharma Inc. is a pharmaceutical company conducting business in more than 70 countries around the world. We are committed to turning innovative science into medical solutions that bring value and hope to patients and their families. Keeping our focus on addressing unmet medical needs and conducting our business with ethics and integrity enables us to improve the health of people throughout the world. For more information on Astellas, please visit our website at www.astellas.com.
This position is based remotely in India. Candidates interested in remote work are encouraged to apply.
Purpose and Scope:
The Clinical Data Engineer (ETL) 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 ETL processes to ingest, transform, and load clinical data from various sources into the data infrastructure. 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.
Essential Job Responsibilities:
Develop and maintain comprehensive data streaming architecture strategies tailored to the needs of Clinical and Operational data management. Design, develop, and maintain ETL (Extract, Transform, Load) processes to efficiently move clinical data from various sources to target systems. Develop and implement data load strategies to ensure design integrity and flexibility. Develop and implement data transformation logic to clean, standardize, and enrich raw clinical data. Optimize data workflows and performance through automation, parallel processing, and data partitioning techniques. Design scalable data pipeline architectures to handle large volumes of clinical data. Develop APIs, interfaces, and middleware solutions for seamless communication between clinical software systems and databases. Ensure data compatibility and compliance with industry standards such as HL7, FHIR, ICH M11, and others. Implement security controls, encryption mechanisms, redaction logic, and access management policies to protect sensitive data from unauthorized access, breaches, and cyber threats. Monitor compliance with healthcare regulations such as HIPAA, GDPR, and other data privacy laws, and implement measures to address potential risks and vulnerabilities. Continuously monitor ETL job performance and make necessary adjustments to improve speed and reliability. Document data flow designs, technical specifications, and operational procedures to facilitate knowledge transfer and support ongoing maintenance and enhancements. Proactively identify and address potential bottlenecks and challenges in data processing workflows. Work closely with cross-functional teams including data mangers, 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 to standardize data practices and ensure compliance with organizational policies. Stay abreast of emerging technologies, trends, and best practices in clinical data management, architecture, and engineering.