Associate Software Engineer

Mayo Clinic•Rochester, MN

1d•Hybrid

About The Position

The Associate Software Engineer is responsible for aiding in the development and maintenance of a technology portfolio. Under the guidance of more experienced software engineering team members, the Associate Software Engineer assists in designing and developing back-end services to support data-centric business, clinical, and analytic applications or databases. These applications may involve cloud computing, big data, mobile technologies, data science, data warehousing, or machine learning, using state-of-the-art software development tools and frameworks. The Associate Software Engineer works closely with the engineering, platform, and solutions teams to develop and support applications as required by business and practice. Participation in DevOps, Agile, and continuous development and integration frameworks is expected. The role involves programming in high-level languages and utilizing deployment automation and configuration management tools. Additionally, the Associate Software Engineer contributes to documenting processes and source code and uses system knowledge and prescribed guidelines to troubleshoot, analyze system issues, and propose resolutions. The Associate Software Engineer plays a role in developing secure, scalable, and reliable software and data solutions by collaborating across technology teams, adhering to established technical standards, and applying best practices. Responsibilities include participating in code reviews, supporting delivery processes with an emphasis on quality and system integrity, and communicating effectively with diverse audiences. The role requires an understanding of software and data delivery processes, including fundamental knowledge of security, integrity, auditability, and system recoverability. Continuous learning and staying current with evolving technologies and industry trends is expected. Mayo Clinic Genomics and Emerging Systems Unit is seeking an Associate Software Engineer to aid in the design, development, and maintenance of robust .NET-based back-end services supporting a broad portfolio of genomics and clinical applications. These systems operate across on-premises environments and modern cloud platforms, including Azure and Google Cloud Platform (GCP), and integrate with distributed services through secure APIs and web services. The Associate Software Engineer will work under the guidance of more senior developers to build and optimize services that handle complex genomic workflows, large-scale clinical datasets, and high-throughput data processing. This includes ensuring that all services meet strict performance, reliability, and accuracy requirements, scale effectively as data volumes grow, and remain resilient within hybrid cloud ecosystems. The role collaborates closely with Senior Developers, Product Owners, Product Managers, Architects, and cross-functional engineering partners to translate requirements into well-architected, maintainable code. Responsibilities include designing and implementing services aligned to enterprise architecture, including cloud-ready APIs, data integration pipelines, and secure interoperability layers for genomic systems. The engineer participates in Agile and DevOps practices using GitHub, Azure DevOps (ADO), Azure Pipelines, and CI/CD frameworks. Work may include deployment automation and configuration management using tools such as ARM/Bicep, Terraform, Cloud Build, or Azure Pipelines, supporting both on-prem and cloud-hosted applications. Development efforts leverage modern .NET technologies, cloud-native patterns, API-first design, and secure coding practices. Responsibilities also include maintaining comprehensive technical documentation, contributing to code reviews, and participating in expert-level troubleshooting through log analysis, root cause evaluation, and data/system investigation. This position requires effective communication with peers, leaders, and clinical partners across the organization. The engineer will continue to build knowledge of genomics workflows, organizational processes, and customer needs while performing a range of technical assignments with moderate guidance and increasing autonomy. The role includes providing 24/7 on-call support.

Requirements

Under the guidance of more experienced software engineering team members.
Programming in high-level languages.
Utilizing deployment automation and configuration management tools.
Understanding of software and data delivery processes, including fundamental knowledge of security, integrity, auditability, and system recoverability.
Adhering to established technical standards.
Applying best practices.
Working under the guidance of more senior developers.
Collaborating closely with Senior Developers, Product Owners, Product Managers, Architects, and cross-functional engineering partners.
Translating requirements into well-architected, maintainable code.
Designing and implementing services aligned to enterprise architecture.
Participating in Agile and DevOps practices using GitHub, Azure DevOps (ADO), Azure Pipelines, and CI/CD frameworks.
Supporting deployment automation and configuration management using tools such as ARM/Bicep, Terraform, Cloud Build, or Azure Pipelines.
Leveraging modern .NET technologies, cloud-native patterns, API-first design, and secure coding practices.
Maintaining comprehensive technical documentation.
Contributing to code reviews.
Participating in expert-level troubleshooting through log analysis, root cause evaluation, and data/system investigation.
Effective communication with peers, leaders, and clinical partners across the organization.
Continuing to build knowledge of genomics workflows, organizational processes, and customer needs.
Performing a range of technical assignments with moderate guidance and increasing autonomy.

Nice To Haves

Cloud computing
Big data
Mobile technologies
Data science
Data warehousing
Machine learning
State-of-the-art software development tools and frameworks
Cloud platforms, including Azure and Google Cloud Platform (GCP)
Integrating with distributed services through secure APIs and web services
Building and optimizing services that handle complex genomic workflows, large-scale clinical datasets, and high-throughput data processing
Ensuring services meet strict performance, reliability, and accuracy requirements
Scaling effectively as data volumes grow
Remaining resilient within hybrid cloud ecosystems
Designing and implementing services aligned to enterprise architecture, including cloud-ready APIs, data integration pipelines, and secure interoperability layers for genomic systems
Deployment automation and configuration management using tools such as ARM/Bicep, Terraform, Cloud Build, or Azure Pipelines
Supporting both on-prem and cloud-hosted applications
Leveraging modern .NET technologies, cloud-native patterns, API-first design, and secure coding practices
Expert-level troubleshooting through log analysis, root cause evaluation, and data/system investigation

Responsibilities

Aiding in the development and maintenance of a technology portfolio.
Assisting in designing and developing back-end services to support data-centric business, clinical, and analytic applications or databases.
Working closely with the engineering, platform, and solutions teams to develop and support applications.
Participating in DevOps, Agile, and continuous development and integration frameworks.
Programming in high-level languages.
Utilizing deployment automation and configuration management tools.
Contributing to documenting processes and source code.
Troubleshooting, analyzing system issues, and proposing resolutions.
Developing secure, scalable, and reliable software and data solutions.
Collaborating across technology teams, adhering to established technical standards, and applying best practices.
Participating in code reviews.
Supporting delivery processes with an emphasis on quality and system integrity.
Communicating effectively with diverse audiences.
Building and optimizing services that handle complex genomic workflows, large-scale clinical datasets, and high-throughput data processing.
Ensuring services meet strict performance, reliability, and accuracy requirements.
Designing and implementing services aligned to enterprise architecture, including cloud-ready APIs, data integration pipelines, and secure interoperability layers for genomic systems.
Participating in Agile and DevOps practices using GitHub, Azure DevOps (ADO), Azure Pipelines, and CI/CD frameworks.
Supporting deployment automation and configuration management.
Maintaining comprehensive technical documentation.
Participating in expert-level troubleshooting through log analysis, root cause evaluation, and data/system investigation.
Providing 24/7 on-call support.