Clinical Data Engineer

Responsibilities :

• Develop and maintain comprehensive data streaming architecture strategies tailored to the needs of Clinical and Operational data management.
• Design, develop, and maintain robust data pipelines to ingest, process, and transform clinical data from various sources.
• Develop and implement data strategies to ensure the accuracy, integrity, and security of clinical data.
• Lead all data engineering tasks and implement ETL (Extract, Transform, Load) processes to ensure efficient data flow and transformation.
• 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.
• 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 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.

Requirements

Qualifications : Required :

Required :

• Bachelor of Science degree in Computer Science, Information Systems, Data Science, or a related field.
• 10+ years of relevant experience working in in data architecture, engineering roles or related roles within a healthcare industry.
• Data architecture and engineering experience

Preferred :

• Master of Science degree in Computer Science, Information Systems, Data Science, or a related field.
• 7+ years’ experience in Life Sciences industry
• Expertise in data pipeline design, data modelling, 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 technologies like Talend, AWS Glue and DataBricks.
• Experience with Master Data Management (MDM) tools like Veeva Network, Reltio and IBM Infosphere
• 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.
• Relevant certifications in cloud computing and data engineering tools / platforms are advantageous.

Benefits :

• Medical, Dental and Vision Insurance
• Generous Paid Time Off options, including Vacation, Sick time, plus national holidays including Heritage Days, and Summer and Winter Breaks
• Country Specific Retirement Savings Plan (401k, RRSP, etc.)
• Company paid life insurance
• Annual Corporate Bonus and Quarterly Sales Incentive for eligible positions
• Long Term Incentive Plan for eligible positions
• Referral bonus program
30+ days ago