Remote Senior Data Engineer - Enterprise Analytics

Mayo Foundation for Medical Education and Research; Rochester (MN); Remote; USD 148,000 - 215,000; Full time

Job summary

Mayo Clinic is seeking an experienced Data/Software Engineer to lead design, development, and delivery of scalable data pipelines and platform capabilities. The role involves mentoring teams, driving production-grade code, and collaborating across engineering disciplines in a remote-friendly environment.

The candidate will work in an Agile/Safe/Scrum setting, utilize modern data tools and cloud platforms, and contribute to data products supporting analytics, AI/ML, and enterprise workloads.

Qualifications

• Bachelor's or Associate degree in computer science/engineering with relevant experience.
• 5+ years in data engineering, data science or analytical modeling.
• Experience leading data engineering teams in CI/CD environments.
• Experience with relational and NoSQL databases.
• Familiarity with cloud platforms (GCP/Azure/AWS) and CI/CD tools.

Responsibilities

• Design, prototype, and develop data pipelines and architecture.
• Lead internal process improvements and automation of workflows.
• Mentor engineers and contribute to production-grade codebase.
• Collaborate across front-end, back-end, and data teams in an Agile environment.

Skills

Python

SQL

Distributed computing

Cloud platforms

CI/CD

IaC

Data pipelines

Data platforms

Education

Bachelor's degree in Computer Science/Engineering or related field

Associate's degree in Computer Science/Engineering or related field

Tools

Jira

GitHub

SharePoint

Azure Boards

Kubernetes

Docker

GCP

AWS

Job description

Mayo Clinic is seeking an experienced Data/Software Engineer to lead design, development, and delivery of scalable data pipelines and platform capabilities. The role involves mentoring teams, driving production-grade code, and collaborating across engineering disciplines in a remote-friendly environment.

The candidate will work in an Agile/Safe/Scrum setting, utilize modern data tools and cloud platforms, and contribute to data products supporting analytics, AI/ML, and enterprise workloads.