Data Science DevOps Engineer (Kubernetes, Linux & Windows)

Yale New Haven Health; Stratford (CT); On-site; USD 90,000 - 130,000; Full time

Job summary

Yale NewHaven Health is seeking an ITS Lead Data Science Dev/Ops Engineer to manage data science platforms and distributed IT environments. The role blends system administration with DevOps, collaborating with analytics teams to deploy scalable, highly available data workflows using Kubernetes on Linux and Windows.

Responsibilities include infrastructure as code with Python, Ansible, Helm, and GitLab; monitoring with Prometheus; and disaster recovery planning across data centers.

Qualifications

• Bachelor's Degree in Healthcare Administration, ITS, or related field preferred.
• 3–4 years of experience in healthcare information technology; 7–10 years in ITS/EHR/data science platforms; healthcare or regulated environment preferred.
• Experience with Kerberos/AD configuration and security in distributed environments.

Responsibilities

• System Management /DevOps: Ubuntu Linux engineering and operations; Kubernetes deployment and management; IaC with Python, Ansible, Helm, GitLab.
• Data Management: develop data inventory for new data sets; participate in data management plans.
• Application Development: assist with defining use cases, enterprise architectures, and healthcare data warehouse access; build tools to automate workflows.

Skills

Linux/Windows administration

Kubernetes

Python

Kerberos/AD configuration

DevOps tooling (Ansible)

Education

Bachelor's degree required

Master's degree preferred

Tools

Ansible

GitLab

Prometheus

Nutanix

Job description

Yale NewHaven Health is seeking an ITS Lead Data Science Dev/Ops Engineer to manage data science platforms and distributed IT environments. The role blends system administration with DevOps, collaborating with analytics teams to deploy scalable, highly available data workflows using Kubernetes on Linux and Windows.

Responsibilities include infrastructure as code with Python, Ansible, Helm, and GitLab; monitoring with Prometheus; and disaster recovery planning across data centers.