Production Operations (ProdOps) Engineer
Introduction:
Production Operations (ProdOps) Engineer to manage and support mission-critical production platforms. The ideal candidate will have strong expertise in GitLab CI/CD, Kubernetes, PostgreSQL, Database Deployments, Application Troubleshooting, Dynatrace Monitoring, and On-Call Production Support. This role requires a proactive individual who can ensure platform stability, automate operational processes, improve deployment efficiency, and rapidly resolve production incidents.
Responsibilities:
- Provide operational support for production and non-production environments.
- Participate in a 24x7 on-call rotation and respond to critical production incidents.
- Monitor system health, application performance, and infrastructure availability.
- Perform root cause analysis (RCA) and implement preventive measures.
- Troubleshoot complex applications, databases, infrastructure, and deployment issues.
- Design, maintain, and optimize GitLab CI/CD pipelines.
- Automate application deployment, testing, and release processes.
- Deploy, configure, and manage containerized applications on Kubernetes.
- Manage scaling, availability, and performance optimization of Kubernetes workloads.
- Plan and execute database deployment activities across environments.
- Support and maintain PostgreSQL databases.
- Configure and maintain monitoring dashboards using Dynatrace.
- Develop automation scripts and operational tooling.
- Create and maintain operational runbooks and standard operating procedures.
Requirements:
Technical Skills:
- GitLab CI/CD
- Kubernetes
- Database Deployments
- Dynatrace
Preferred Qualifications:
- Bachelor's degree in computer science, Information Technology, or related field.
- 5+ years of experience in Production Support, DevOps, SRE, or Platform Engineering roles.
- Experience with Linux administration and shell scripting.
- Familiarity with cloud platforms such as Azure, AWS, or Google Cloud Platform.
- Experience with Infrastructure as Code (Terraform preferred).
- Understanding of microservices architecture and containerization technologies.
Success Metrics:
- Production availability and up time.
- Mean Time to Detect (MTTD) and Mean Time to Resolve (MTTR).
- Deployment success rate.
- Reduction in recurring incidents.
- Platform reliability and performance improvements.
- Operational automation and efficiency gains.
Keywords:
GitLab CI/CD, Kubernetes, PostgreSQL, Database Deployments, Dynatrace, Production Support, Incident Management, Troubleshooting, On-Call Support, DevOps, SRE, Platform Engineering, Monitoring, Release Management, Automation.
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