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# Devops Engineer - INTL India

- **Company:** Insight Global
- **Location:** Woonsocket, RI, United States
- **Experience:** Experienced
- **Salary:** $18,720.0 - $29,120.0
- **Contract:** Permanent contract
- **Skills:** Continuous Integration, Data Validation, Information Engineering, DevOps, Python (Programming Language), Standard Sql, Cloud Platform System, Delivery Pipeline, Software Troubleshooting, Kubernetes, Deployment Automation, Data Management
- **Published:** August 23, 2026
- **Apply:** https://dejobs.org/x/x/8A25B564F9A6457992F073148814DA4D/job/

## About the Role

4-5 years of professional experience in DevOps

Experience building and supporting CI/CD pipelines.

Hands-on experience with Kubernetes in production environments.

Working knowledge of Python for automation and scripting.

SQL skills for troubleshooting and data validation.

Experience implementing security frameworks, controls, or best practices within deployment pipelines and cloud environments.

Strong troubleshooting and problem-solving skills.

Self-starter capable of driving projects forward with limited supervision.

Excellent communication and collaboration skills.

Proactive in providing project updates and escalating support needs when necessary.

Demonstrated ownership and accountability for assigned work.

Curious mindset with a desire to understand the broader business and technical impact of projects. Experience working on a Platform Engineering team

## Description

We are seeking a DevOps Engineer to support a strategic platform initiative supporting Data Science and Data Engineering teams. This individual will help streamline application and infrastructure deployments, improve CI/CD processes, and ensure secure, scalable delivery of data platforms. The ideal candidate is a proactive problem solver who thrives in collaborative environments, communicates effectively, and takes ownership of deliverables with minimal oversight., Design, implement, and maintain CI/CD pipelines to support application and platform deployments.

Support Kubernetes-based environments and deployment automation initiatives.

Partner closely with Data Engineering and Data Science teams to enable efficient, secure release processes.

Implement and maintain deployment security controls and best practices.

Develop and maintain automation scripts using Python.

Troubleshoot deployment issues and work across teams to resolve blockers.

Track assigned work, provide regular status updates, and proactively communicate risks or support needs.

Drive initiatives independently while collaborating effectively with cross-functional stakeholders.

Continuously identify opportunities to improve platform reliability, scalability, and deployment efficiency.


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