About the role
We are looking for a hands-on DevOps Platform Engineer to build, automate, and manage cloud infrastructure and deployment pipelines for enterprise-scale data platforms. The ideal candidate will have strong experience in AWS, CI/CD, infrastructure automation, and DevOps best practices, along with exposure to data engineering ecosystems.
Responsibilities:
- Build, maintain, and optimize highly available cloud infrastructure on AWS.
- Design and manage end-to-end CI/CD pipelines using Jenkins and related DevOps tools.
- Automate infrastructure provisioning, deployments, monitoring, and operational processes.
- Manage source code repositories and release processes using Git and SCM tools.
- Support data engineering and analytics teams by enabling reliable platform operations.
- Perform infrastructure governance, audits, security reviews, and compliance checks.
- Develop automation scripts using Python and Shell scripting.
- Create technical design documentation and operational runbooks.
- Collaborate with engineering teams to identify, design, and implement scalable platform solutions.
- Troubleshoot production issues and ensure platform reliability and uptime.
Requirements:
- 3-5 years of hands-on experience in DevOps, Cloud Engineering, or Platform Engineering.
- Strong understanding of AWS cloud infrastructure and automation.
- Experience working with enterprise-scale data platforms and analytics environments.
- Ability to work cross-functionally with engineering, data, and business teams.
- Strong problem-solving, documentation, and stakeholder management skills.
Must-Haves:
- AWS Cloud Services (EC2 S3 IAM, VPC, Lambda, CloudWatch)
- Jenkins and CI/CD Pipeline Development
- Git / Version Control Systems
- Infrastructure Automation and Deployment Management
- Python and Shell Scripting
- Linux Administration
- Infrastructure Monitoring and Troubleshooting
- DevOps Best Practices
- Production Release Management
- Cloud Security and Governance
Preferred Skills:
- Apache Airflow
- Cloudera Ecosystem
- Terraform / Infrastructure as Code
- Docker and Kubernetes
- Data Platform / Data Engineering exposure