Senior Site Reliability Engineer

MindBrain

0 years

0 Lacs

India

Posted:4 days ago| Platform:

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Skills Required

reliability programming linux networking azure architecture containerization orchestration docker kubernetes code terraform monitoring splunk integration github ml databricks saas communication development documentation management analysis scalability automation certifications engineering devops microservices ai

Work Mode

On-site

Job Type

Contractual

Job Description

Position SITE Reliability Engineer

Budget- 1.7 LPM

Exp- 10 yrs

Duration- 6 months

Technical Skills:

Programming: Proficiency in languages like Python.
Operating Systems: Deep understanding of Linux/Windows operating systems and networking concepts.
Cloud Technologies: Experience with Azure including services, architecture, and best practices.
Containerization and Orchestration: Hands-on experience with Docker, Kubernetes, and related tools.
Infrastructure as Code (IaC): Familiarity with tools like Terraform, CloudFormation or Azure CLI.
Monitoring and Observability: Experience with tools like Splunk, New Relic or Azure Monitoring.
CI/CD: Experience with continuous integration and continuous delivery pipelines, GitHub, GitHub Actions.
Knowledge in supporting Azure ML, Databricks and other related SAAS tools.
Soft Skills:
Problem-Solving: Ability to troubleshoot and debug complex distributed systems independently.
Communication: Strong written and verbal communication skills to collaborate with development and operations teams, and able to write documentation like Runbook etc.
Specific Experience:
Incident Management: Experience with incident response, root cause analysis, and post-incident reviews.
Scalability and Performance: Understanding of scalability, availability, and performance monitoring for large-scale systems.
Automation: Experience in automating repetitive tasks and workflows.
Preferred Qualifications:
Experience with specific cloud platforms ( Azure).
Certifications related to cloud engineering or DevOps.
Experience with microservices architecture including supporting AI/ML solutions.
Experience with large-scale system management and configuration.

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