Responsibilities and Accountabilities :
- Support developing and maintaining comprehensive architecture strategies tailored to the needs of maintain clinical trial data analysis and submission.
- Oversee the installation, configuration, and maintenance of statistical computing environments (e.g., SAS)
- Develop and implement data strategies to ensure the accuracy, integrity, and security of clinical data.
- Provide technical support and guidance to users of the statistical computing environment.
- Work closely with other DigitalX members and data professionals to integrate the statistical computing environment with other systems and workflows.
- Support designing scalable SCE architectures to manage large volumes of clinical data including real world data.
- Oversee development of APIs, interfaces, and middleware solutions for seamless communication between clinical software systems and databases.
- Lead or participate in projects related to system upgrades, migrations, or new implementations.
- Monitor system health, data integrity, and performance metrics using monitoring tools and implement proactive measures to address issues and bottlenecks.
- Liaise with software vendors and service providers to address issues, manage licenses, and negotiate contracts.
- Manage project timelines, and deliverables.
- Stay updated on industry trends and advancements to recommend and implement new tools or practices.
Requirements
Required Qualifications :
Bachelor of Science degree in Computer Science, Information Systems, Data Science, or a related field.Minimum of 5 years of relevant experience working in in data architecture, engineering roles or related roles within a healthcare industry.Experience in statistical computing environments such as SAS, or similar toolsPreferred Qualifications :
Master of Science degree in Computer Science, Information Systems, Data Science, or a related field.5+ years’ of demonstrated experience in Life Sciences industry.Knowledge of operating systems (e.g., Linux, Windows) and experience in system configuration, maintenance, and troubleshootingProficiency in programming languages commonly used in data management and analysis, such as SQL, SAS, R.Understanding of networking concepts and security practices to safeguard data and systems.Experience in managing projects related to system upgrades, installations, or integrations.In-depth understanding of life sciences business processes, adept at translating business requirements into effective technical solutions.Experience with Agile methodology and mindset.Excellent verbal and written communication skills to interact with users, stakeholders, and vendors effectively.Project management capabilities, ensuring adherence to timelines for successful solution delivery.Demonstrated leadership skills, including guiding technical teams, offering mentorship, and influencing architectural decisions.