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We are seeking a detail-oriented Cloud Engineer QA with expertise in infrastructure validation, cloud migration testing, and platform quality assurance for On-Premises to GCP migration programs. The ideal candidate should have 3 to 5 years of experience in cloud infrastructure QA, automation testing, environment validation, and production readiness testing. The candidate will work closely with infrastructure, DevOps, and data engineering teams to ensure successful migration, system reliability, performance, and compliance throughout cloud transformation initiatives. Thai language proficiency is mandatory.
Job Responsibility
Validate infrastructure migration activities from On-Premises to GCP environments
Perform functional, integration, regression, and performance testing for cloud infrastructure and cloud-native data platforms
Validate environments and deployments involving Spark, Airflow, Kafka, BigQuery, MongoDB, Redis, Dataproc, Dataplex, and Agent Platform Workbench
Design and execute automated QA processes for infrastructure deployments and cloud services
Validate CI/CD pipelines, deployment workflows, and release quality
Perform environment verification, security validation, and configuration testing
Collaborate with DevOps, infrastructure, and data teams during migration projects
Identify defects, bottlenecks, and performance issues across cloud systems
Support production readiness testing and operational validation
Participate in root cause analysis and issue resolution activities
Requirements
3 to 5 years of experience in cloud infrastructure QA
automation testing
environment validation
production readiness testing
Experience in cloud infrastructure testing and QA processes
Knowledge of Google Cloud Platform (GCP) services and cloud-native architectures
Experience validating migrations from On-Premises to Cloud environments
Familiarity with Spark, Airflow, Kafka, BigQuery, MongoDB, Redis, Dataproc, Dataplex, and Agent Platform Workbench
Understanding of CI/CD pipelines and automation testing frameworks
Familiarity with Kubernetes, Docker, and containerized environments
Experience with monitoring, logging, and observability tools
Strong analytical and troubleshooting skills
Experience with API testing and environment validation