Cloud Support Engineer

4 days ago

Bengaluru, Karnataka, India DMart Full time ₹ 6,00,000 - ₹ 18,00,000 per year

About the Role

We are looking for a Cloud Support Engineer with strong hands-on experience in Google Kubernetes Engine (GKE), Kubernetes, and data pipeline orchestration. The role involves supporting, troubleshooting, and optimizing cloud-native workloads and data flow systems across production and non-production environments.

You will work closely with developers, DevOps, and data engineering teams to ensure high availability, scalability, and performance of our containerized and data-driven applications.

Key Responsibilities

  • Cloud Infrastructure Support:

  • Manage and support workloads running on Google Cloud Platform (GCP), primarily using GKE.

  • Monitor and maintain clusters, nodes, and deployments for optimal performance.

  • Kubernetes Operations:

  • Handle deployment, scaling, and troubleshooting of containerized applications.

  • Implement and maintain CI/CD pipelines integrated with Kubernetes.

  • Define and enforce Kubernetes resource limits, namespaces, and policies.

  • Data Pipelines & Workflow Support:

  • Support and optimize data ingestion and transformation pipelines (e.g., using Apache Beam, Dataflow, Airflow, or similar tools).

  • Monitor job executions, troubleshoot failures, and ensure timely data delivery.

  • Automation & Observability:

  • Implement monitoring, alerting, and logging solutions (e.g., Prometheus, Grafana, Stackdriver, ELK).

    Automate repetitive tasks using scripts and infrastructure-as-code (e.g., Terraform, Helm).

  • Incident Management & Root Cause Analysis:

  • Respond to production incidents and work on prevention measures.

    Collaborate with engineering teams to drive long-term reliability improvements.

Required Skills & Experience

  • Strong experience with Kubernetes and GKE in production environments.
  • Experience in GCP.
  • Solid understanding of containerization (Docker) and microservice architectures.
  • Hands-on experience in data pipeline management (Airflow, Dataflow, Beam, or equivalent).
  • Knowledge of CI/CD tools (Jenkins, GitLab CI, Cloud Build, ArgoCD).
  • Experience with monitoring and logging tools such as Prometheus, Grafana, or Stackdriver.
  • Familiarity with Terraform, Helm, or other IaC tools.

    Good understanding of networking, load balancing, and security in cloud environments.
  • Proficiency in Python, Bash, or Go for scripting and automation.

Preferred Qualifications

  • GCP Professional Cloud Engineer or CKA (Certified Kubernetes Administrator) certification.
  • Azure Cloud setup
  • Exposure to multi-cloud or hybrid-cloud setups.
  • Experience supporting real-time or batch data systems.
  • Familiarity with DevOps and SRE principles.

Soft Skills

  • Strong problem-solving and analytical skills.
  • Ability to work collaboratively in cross-functional teams.
  • Good communication and documentation skills.
  • A proactive attitude towards learning and automation.

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