Job Description :
Job requirement: Performance engineering expert needed for a large scale mainframe to AWS cloud migration project with critical non-functional requirement. He will be responsible to identify performance bottlenecks of the target cloud native architecture and recommend tuning strategies. The candidate should be able design, execute, monitor performance tests, perform root cause analysis of performance bottlenecks and advice tuning measures in the overall architecture. The migrated application stack consists of following technologies – Springboot, Kubernetes, Kafka, Redis, S3, Airflow. The application supports high volume real time and batch transaction processing. Looking for candidate with intimate familiarity and experience in performance engineering of such eco-system. Skillset required: · Deep insight in performance testing tools techniques and strategies for a cloud native microservice based architecture for both real time and batch data processing. · Hands-on experience in building performance test automation. · Hands-on experience (>5 Yesr) in developing cloud native microservices using SpringBoot · Experienced and deep understanding of GRPC based microservices. · Hands-on experience in application development and tuning in Kubernetes environment. · Hands-on understanding of Java runtime environment and its performance traits and tuning. · Hands-on experience in setting up monitoring services using Prometheus and Grifana based observability framework · Deep understanding of large scale event driven architecture using Kafka event bus. · Hands-on in Kafka performance optimization for large scale event bus · Deep insight about performance optimization of mission critical high volume data caching architecture using Redis. · Expert in AWS services like EKS, MKS, EC2, RDS, DynamoDB, S3, CloudWatch, Athena, Glue, Quicksight. · Expert in DevOps processes and familiar with Jenkins Pipeline. · Experienced in SCRUM process. · Should be able to interact directly with client. · Great team player.
             

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