Responsabilities
the qa test engineer will be responsible for ensuring the quality, reliability, and performance of enterprise systems and integrations across salesforce data cloud, aws, apis, and data pipelines. The ideal candidate has hands-on experience with test automation frameworks, sql-based data validation, copado test management, and etl process verification. The qa test engineer will work closely with developers, data engineers, and product teams to design, execute, and maintain robust test suites and automation schedules that support continuous integration and deployment.
Test planning & case development
develop comprehensive test plans, test cases, and test data based on business and technical requirements.
Define test coverage and acceptance criteria for integrations, apis, and data workflows.
Document and maintain traceability between test cases and requirements.
Testing & validation
execute functional, integration, regression, performance, and uat tests across platforms (e.g., salesforce, aws)
validate data integrity across etl pipelines, apis, and sql-based data stores.
Conduct salesforce data cloud testing, including data ingestion, transforms, ir, and segmentation outcomes.
Verify api integrations between salesforce, aws services, and third-party systems.
Automation & tools
build, maintain, and optimize automated test suites for backend and integration testing.
Utilize copado for test automation, change management, and deployment validation within the ecosystem.
Implement automation using python, postman, or similar frameworks for api and ui testing.
Configure and monitor scheduled test executions as part of ci/cd pipelines.
Data validation & etl testing
write and execute complex sql queries to validate data quality, transformation accuracy, and completeness.
Collaborate with data engineers to test and validate etl workflows (aws glue, lambda, step functions, etc.).
Ensure synchronization and accuracy of data between aws and salesforce data cloud.
Environment & scheduling management
coordinate test environments and data refresh schedules to support multiple releases and sprints.
Develop automated scheduling of regression suites to support ongoing platform stability.
Participate in release readiness activities and production validation.
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