Computer Scientist 1

5 - 6 years

14 - 18 Lacs

Posted:6 months ago| Platform: Naukri logo

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Job Type

Full Time

Job Description

  • Architecting, deploying, and maintaining Kubernetes clusters to meet organizational standards.
  • Leading containerized applications using Kubernetes, including pod scheduling, scaling, and rolling deployments.
  • Developing and maintaining automation scripts and tools for provisioning and configuring Kubernetes infrastructure, strictly adhering to infrastructure-as-code principles.
  • Setting up monitoring tools and implementing alerting mechanisms to ensure the health and performance of Kubernetes clusters.
  • Investigating and resolving issues related to Kubernetes infrastructure, networking, and application deployments.
  • Implementing security measures to safeguard Kubernetes clusters, ensuring compliance with industry standards.
  • Identifying and optimizing performance bottlenecks for efficiency and scalability.
  • Analyzing resource usage patterns and forecasting capacity requirements.
  • Collaborating with cross-functional teams to support application deployment and integration with Kubernetes.
  • Documenting processes, configurations, and procedures to swiftly address issues.
  • Staying updated with the latest developments in Kubernetes and related technologies.
  • Implementing disaster recovery strategies to ensure business continuity.
  • Providing mentorship and training to junior team members on Kubernetes technologies and standard processes.
Requirements
  • B.Tech / M.Tech degree in Computer Science from a premier institute.
  • 5+ years of proven experience in software development and operations.
  • Strong computer science fundamentals and understanding of architecture, design, and performance.
  • Good understanding of Cloud Platforms, with a preference for AWS.
  • Proficient in Python/Go and Shell scripting.
  • Hands-on experience in writing reliable and maintainable code.
  • Strong problem-solving skills and ability to work independently.
  • Good understanding of Kubernetes and product life cycles.
  • Technical depth in operating systems, computer architecture, and OS internals.
  • Technical depth in Cloud Computing, Cloud Platforms, and Services architecture.

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