We are seeking a highly skilled Senior DevOps & Infrastructure Consultant to lead the design, implementation, and optimization of our cloud-native infrastructure.

You will be the bridge between development and operations, ensuring our systems are scalable, resilient, and highly automated.

The ideal candidate has deep expertise in Kubernetes, a passion for Infrastructure as Code (IaC), and a background in managing complex distributed data systems.

Key Responsibilities :

- Orchestration & Automation: Design and manage production-grade Kubernetes clusters, ensuring high availability, security, and efficient resource utilization.

- Infrastructure as Code: Automate the provisioning and configuration of global infrastructure using tools like Terraform, Ansible, Chef, or Puppet.

- CI/CD Pipeline Development: Build and maintain robust CI/CD pipelines to streamline the deployment of services written in Go, Python, and Java.

- Database & Data Stream Management: Maintain and optimize distributed data stores including MongoDB, Redis, Cassandra, Elasticsearch, and Kafka.

- Scripting & Tooling: Develop custom scripts and internal tools to automate repetitive tasks and improve system observability.

- Consulting & Mentorship: Act as a technical subject matter expert, guiding development teams on best practices for cloud-native architecture and infrastructure security.

- Performance Monitoring: Proactively monitor system performance and troubleshoot complex architectural bottlenecks across the stack.

Technical Requirements :

Education : B.Tech / B.E. degree in Computer Science or an equivalent software engineering degree/experience.

Experience : Minimum 6 years of professional experience in a DevOps, SRE, or Infrastructure Consulting role.

Orchestration :

- Expert-level knowledge of Kubernetes (EKS, GKE, or Bare Metal).

IaC & Config :

- Deep expertise in Terraform and Ansible (or Chef/Puppet).

Programming :

- Proficiency in Python or Go; familiarity with Java environments.

Databases :

- Hands-on experience with Mongo, Redis, Cassandra, and Elasticsearch.