Clinical Data Architect & Engineer

Astellas Pharma - Markham, IL

Full-time - Mid Level

Markham, IL

10,001+ employees

Management of Companies and Enterprises

About the position

The Clinical Data Architect and Engineer role at Astellas Pharma Canada is pivotal in fostering innovation and operational efficiency within the life sciences sector. This position is designed to facilitate data-driven decision-making processes, expedite drug discovery initiatives, and enhance regulatory compliance efforts. The successful candidate will be responsible for designing and implementing customized data architecture solutions that address the complexities inherent in life sciences research and development. This includes supervising the integration and management of various data sources, such as clinical trials data, operational data, genomic data, and real-world evidence. In this role, the Clinical Data Architect and Engineer will collaborate closely with research scientists, statisticians, clinicians, regulatory experts, and DigitalX professionals. The objective is to establish and uphold robust data architecture frameworks that align with business objectives, regulatory mandates, and industry standards. The position requires expertise in Data Engineering, Data Modeling, and Business Intelligence (BI) technologies, as well as adept management of governance processes to maintain the integrity, security, and accessibility of data assets. This strategic role is essential in advancing Astellas' mission by leveraging data to drive scientific progress, improve patient outcomes, and efficiently introduce groundbreaking therapies to the market. Key responsibilities include developing comprehensive data architecture strategies, designing scalable databases, implementing data models and integration frameworks, leading data engineering tasks, optimizing data workflows, and ensuring compliance with industry standards. The role also involves monitoring system health, conducting performance tuning, and providing guidance and mentorship to team members. Staying abreast of emerging technologies and identifying opportunities for process improvement are also critical components of this position.

Responsibilities

• Develop and maintain comprehensive data architecture strategies tailored to the unique needs of Clinical and Operational data management.
• Design scalable, efficient, and secure databases, data warehouses, and data lakes to store and manage clinical data effectively.
• Define and implement data models, schemas, and integration frameworks to ensure the integrity and accessibility of clinical data.
• Lead all data engineering tasks and implement data pipelines, ETL processes to ingest, transform, and load clinical data from various sources into the data infrastructure.
• Optimize data workflows and performance through automation, parallel processing, and data partitioning techniques.
• Collaborate with data scientists and analysts to support advanced analytics, machine learning, and predictive modeling initiatives.
• Integrate disparate clinical systems, applications, and data sources to enable interoperability and data exchange across the life sciences ecosystem.
• Develop APIs, interfaces, and middleware solutions for seamless communication between clinical software systems and databases.
• Ensure compatibility and compliance with industry standards such as HL7, FHIR, and others.
• Implement security controls, encryption mechanisms, 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.
• Conduct performance tuning and optimization of databases, queries, and data processing pipelines to enhance efficiency, reliability, and scalability.
• Monitor system health, data integrity, and performance metrics using monitoring tools and implement proactive measures to address issues and bottlenecks.
• Document data architecture designs, technical specifications, and operational procedures to facilitate knowledge transfer and support ongoing maintenance and enhancements.
• Provide guidance, training, and mentorship to team members and stakeholders on best practices in data management, architecture, and engineering.
• Work closely with cross-functional teams including statisticians, statistical programmers, researchers, DigitalX members, and regulatory experts to understand requirements and priorities for clinical data management and analysis.
• Communicate effectively with stakeholders to ensure alignment of data architecture and engineering solutions with organizational goals and objectives.
• Stay abreast of emerging technologies, trends, and best practices in clinical data management, architecture, and engineering.
• Identify opportunities for process improvement, automation, and innovation to enhance the efficiency and effectiveness of data management practices.

Requirements

• Expertise in database design, data modeling, and data integration techniques.
• Proficiency in programming languages commonly used in data management and analysis, such as SQL, SAS, Python, or R.
• Expertise in working with databases and data warehousing technologies like SQL Server, Oracle, MySQL, AWS Redshift, Azure Synapse, Google BigQuery etc.
• Strong command in ETL and Data Integration tools like Talend, AWS Glue and DataBricks.
• Experience with Master Data Management (MDM) tools like Veeva Network, Reltio and IBM Infosphere.
• Experience with BI tools like QlikSense, Tableau and PowerBI.
• In-depth understanding of life sciences business processes, adept at translating business requirements into effective technical solutions.
• Innovative problem-solving abilities for addressing complex data-related challenges.
• Experience with Agile methodology and mindset.
• Excellent communication and interpersonal skills, enabling effective collaboration with cross-functional teams, business stakeholders, and technical experts.
• Project management capabilities, ensuring adherence to timelines for successful solution delivery.
• Demonstrated leadership skills, including guiding technical teams, offering mentorship, and influencing architectural decisions.
• Demonstrated commitment to staying current with the latest trends, technologies, and best practices in the data and analytics field.
• Relevant certifications in cloud computing and data analytics tools/platforms are advantageous.
• Bachelor of Science degree in Computer Science, Information Systems, Data Science, or a related field.
• 10+ years of relevant experience working in data architecture, engineering roles or related roles within a healthcare industry.

Nice-to-haves

• 7+ years' experience in Life Sciences industry
• Master of Science degree in Computer Science, Information Systems, Data Science, or a related field.
• Advanced Analytics experience.