Clinical Data Engineer (SCE)

· 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.

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 tools

Preferred 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 troubleshooting

· Proficiency 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.