SDET & Backend QA Engineer

As an SDET / Backend QA Engineer, you will be responsible for ensuring the quality and reliability of backend services and APIs. You will play a crucial role in designing scalable testing solutions for high-performance, event-driven systems leveraging AWS and Kafka. Key Responsibilities: - Design, develop, and maintain automated test frameworks using Python and Pytest. - Perform API and backend service testing including functional, integration, regression, and performance testing. - Validate distributed systems built on Kafka, AWS services, and serverless architectures. - Develop test strategies for microservices and event-driven systems. - Write and execute test cases for REST APIs and backend workflows. - Implement testing for AWS serverless services such as Lambda, API Gateway, Step Functions, etc. - Integrate automated tests into CI/CD pipelines using GitLab and Jenkins. - Monitor applications and test environments using Grafana and CloudWatch. - Collaborate closely with developers, DevOps, and product teams to ensure high-quality releases. - Ensure end-to-end quality engineering practices across backend systems. Mandatory Skills: Core Technical Skills: - Strong programming skills in Python. - Experience with Pytest for automation testing. - Hands-on experience with AWS (especially Serverless services like Lambda, API Gateway) and Kafka in Unix/Linux environments. Testing Expertise: - Proven experience as SDET with strong API and backend service testing. - Experience in functional, integration, and regression testing, automation frameworks, and test design for microservices and distributed system testing. Cloud & Distributed Systems: - Experience with AWS Serverless architecture. - Understanding of event-driven systems and message queues like Kafka/Kinesis. Additional Company Details: The company also values Secondary Skills as Nice to Have in the following areas: Databases & Data Platforms: - Oracle, SQL Server, Teradata, Athena, DynamoDB. - AWS Streaming Services: Kinesis, API Gateway, CloudWatch. Big Data & Workflow Tools: - EMR, AWS Step Functions. DevOps & Monitoring: - Experience in CI/CD pipelines. - Hands-on exposure to monitoring tools like Grafana. Tools & Platforms: - CI/CD: GitLab, Jenkins. - Monitoring: Grafana, CloudWatch. - Test Management: Jira, X-Ray. - Backend Quality Engineering practices and tools. As an SDET / Backend QA Engineer, you will be responsible for ensuring the quality and reliability of backend services and APIs. You will play a crucial role in designing scalable testing solutions for high-performance, event-driven systems leveraging AWS and Kafka. Key Responsibilities: - Design, develop, and maintain automated test frameworks using Python and Pytest. - Perform API and backend service testing including functional, integration, regression, and performance testing. - Validate distributed systems built on Kafka, AWS services, and serverless architectures. - Develop test strategies for microservices and event-driven systems. - Write and execute test cases for REST APIs and backend workflows. - Implement testing for AWS serverless services such as Lambda, API Gateway, Step Functions, etc. - Integrate automated tests into CI/CD pipelines using GitLab and Jenkins. - Monitor applications and test environments using Grafana and CloudWatch. - Collaborate closely with developers, DevOps, and product teams to ensure high-quality releases. - Ensure end-to-end quality engineering practices across backend systems. Mandatory Skills: Core Technical Skills: - Strong programming skills in Python. - Experience with Pytest for automation testing. - Hands-on experience with AWS (especially Serverless services like Lambda, API Gateway) and Kafka in Unix/Linux environments. Testing Expertise: - Proven experience as SDET with strong API and backend service testing. - Experience in functional, integration, and regression testing, automation frameworks, and test design for microservices and distributed system testing. Cloud & Distributed Systems: - Experience with AWS Serverless architecture. - Understanding of event-driven systems and message queues like Kafka/Kinesis. Additional Company Details: The company also values Secondary Skills as Nice to Have in the following areas: Databases & Data Platforms: - Oracle, SQL Server, Teradata, Athena, DynamoDB. - AWS Streaming Services: Kinesis, API Gateway, CloudWatch. Big Data & Workflow Tools: - EMR, AWS Step Functions. DevOps & Monitoring: - Experience in CI/CD pipelines. - Hands-on exposure to monitoring tools like Grafana. Tools & Platforms: - CI/CD: GitLab, Jenkins. - Monitoring: Grafana, CloudWatch. - Test Management: Jira, X-Ray. - Backend Quality Engineering practices and tools.