AVP - QA Automation Engineer - IB Tech & CRM/ Analytics

QA Automation Engineer – Job Description

Responsibilities:

• Automation Testing:
  • Build and maintain automated test suites using Playwright or Selenium (TypeScript/Java).
  • Develop automation scripts in Python, Java, or similar languages.
  • Implement service-level automation using RestAssured with Java.
• Microservices Testing:
  • Hands-on experience testing Microservices architecture.
  • Ability to automate tests for Java Spring Boot services.
• Functional Testing:
  • Execute end-to-end functional testing and ensure comprehensive test coverage.
  • Hands-on experience with ETL-to-UI workflows.
• ETL & Database Testing:
  • Perform data validation and backend testing across SQL Server, MySQL, and NoSQL databases (MongoDB, Cassandra).
  • Validate data pipelines involving SQL → NoSQL → Cloud buckets.
  • Experience in automating data pipeline testing.
• Big Data & Streaming:
  • Familiarity with Kafka or similar messaging/streaming platforms for data flow validation.
• Cloud & Data Warehousing:
  • Experience with Amazon Redshift, AWS RDS, and cloud storage solutions.
• Version Control:
  • Manage codebase and test scripts using Git.
• Test Management & CI/CD:
  • Organize test cases in QTest and integrate with CI/CD pipelines (Bitbucket, Bamboo, Git Actions).
• API Testing:
  • Perform API testing using Postman and implement API automation frameworks.
• Agile & Collaboration:
  • Work in Scrum teams, use JIRA for bug tracking and task management.
  • Document processes and collaborate via Confluence.

Tools & Technologies:
Playwright, Selenium, RestAssured, Python, Java, Spring Boot, Git, QTest, Bitbucket, Bamboo, Postman, Kafka, Redshift, RDS, MongoDB, Cassandra, AWS Cloud Services.

Preferred Skills:

• Experience with Docker and Kubernetes for containerized test environments.
• Knowledge of CI/CD best practices and pipeline optimization.
• Familiarity with performance testing tools (e.g., JMeter, Gatling).
• Exposure to data streaming and real-time validation using Kafka or similar tools.
• Understanding of AWS services beyond RDS/Redshift (e.g., S3, Lambda).
• Strong analytical and troubleshooting skills for complex data flows.
• Ability to write custom utilities or frameworks for automation in Python/Java.

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