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About the Role :

We are looking for a highly skilled and motivated Cloud Backend Engineer with 4- 7 years of experience, who has worked extensively on at least one major cloud platform (GCP, AWS, Azure, or OCI). Experience with multiple cloud providers is a strong plus. As a Senior Development Engineer, you will play a key role in designing, building, and scaling backend services and infrastructure on cloud-native platforms.

Experience with Kubernetes is mandatory.

Key Responsibilities :

- Design and develop scalable, reliable backend services and cloud-native applications.

- Build and manage RESTful APIs, microservices, and asynchronous data processing systems.

- Deploy and operate workloads on Kubernetes with best practices in availability, monitoring, and cost-efficiency.

- Implement and manage CI/CD pipelines and infrastructure automation.

- Collaborate with frontend, DevOps, and product teams in an agile environment.

- Ensure high code quality through testing, reviews, and documentation.

Required Skills :

- Strong hands-on experience with Kubernetes of atleast 2 years in production environments (mandatory).

- Expertise in at least one public cloud platform [GCP (Preferred), AWS, Azure, or OCI].

- Proficient in backend programming with Python, Java, or Kotlin (at least one is required).

- Solid understanding of distributed systems, microservices, and cloud-native architecture.

- Experience with containerization using Docker and Kubernetes-native deployment workflows.

- Working knowledge of SQL and relational databases.

Preferred Qualifications :

- Experience working across multiple cloud platforms.

- Familiarity with infrastructure-as-code tools like Terraform or CloudFormation.

- Exposure to monitoring, logging, and observability stacks (e.g., Prometheus, Grafana, Cloud Monitoring).

- Hands-on experience with BigQuery or Snowflake for data analytics and integration.

Nice to Have :

- Knowledge of NoSQL databases or event-driven/message-based architectures.

- Experience with serverless services, managed data pipelines, or data lake platforms.