Scientific Programmer

Scientific Programmer III

The Scientific Programmer III develops and modernizes cloud-based software solutions that support large-scale scientific data systems and archive workflows in a remote work environment. This role focuses on migrating applications to AWS, developing Python applications, and implementing CI/CD automation to improve the reliability, scalability, and performance of scientific data processing.

Success in this role means delivering robust, well-documented solutions that efficiently manage complex scientific datasets while collaborating with scientists, engineers, and cloud architects to develop innovative, high-performing software.

What You Will Do in This Role

The Scientific Programmer III will design, develop, and optimize cloud-based software and automation solutions that support scientific data processing, modernize applications, and ensure reliable, scalable systems through collaboration, CI/CD, and AWS technologies.

Responsibilities include:

• Design, develop, test, and maintain software that supports scientific data processing and archive workflows.
• Develop and maintain Python-based applications and automation tools.
• Build and enhance CI/CD pipelines to support automated software development, testing, and deployment.
• Support the migration of scientific applications and workflows from on-premises environments to AWS.
• Collaborate with scientists, software engineers, cloud architects, and system administrators to implement scalable cloud solutions.
• Develop solutions for processing, storing, and managing large scientific datasets using modern cloud technologies.
• Troubleshoot and resolve application, workflow, and deployment issues to ensure reliable system performance.
• Research, evaluate, and implement new technologies that improve system performance, scalability, and maintainability.
• Create and maintain technical documentation, software designs, and operational procedures.
• Participate in Agile development activities including sprint planning, code reviews, and team collaboration.
• Perform other duties and responsibilities as assigned.

What You Will Bring

Required qualifications:

• Bachelor's degree in Computer Science, Software Engineering, Data Science, a related technical discipline, or equivalent work experience.
• Eight (8) or more years of experience developing scientific or data-intensive software applications.
• Experience developing applications using Python.
• Experience supporting CI/CD pipelines and software automation.
• Experience working in Amazon Web Services (AWS) cloud environments.
• Experience with cloud-native application development and infrastructure automation.
• Familiarity with scientific data processing and large-scale data management.
• Experience working in Agile/Scrum software development environments.
• Strong analytical, troubleshooting, written, and verbal communication skills.

Preferred qualifications:

• Experience migrating applications or workflows from on-premises infrastructure to AWS.
• Experience with data lake architectures, data mesh concepts, or other modern data management approaches.
• Experience working with large-scale archive systems or scientific data repositories.
• Experience with Infrastructure as Code (e.g., Terraform, AWS CloudFormation, or AWS CDK).
• Familiarity with Git-based source control and DevOps best practices.
• Experience supporting high-performance computing (HPC) or distributed computing environments.

Work authorization/security clearance requirements:

• Ability to obtain a security clearance.

Work Environment:

• This work is normally completed in a remote environment.

Physical Demands:

• Prolonged periods of sitting at a desk and working on a computer.
• Must be able to access and navigate each department at the organization's and client facilities.

Travel Required:

• No

Proficiency Requirement:

• The employee is expected to demonstrate proficiency in all essential job functions, tools, and processes related to this position within the first 90 days of employment. This includes acquiring a thorough understanding of job-specific responsibilities, systems, and workflows as outlined during onboarding and training. Failure to meet this requirement may result in additional training, reassessment, or other actions as deemed necessary by management.