Lead QA Engineer (Automation & Performance Focus)

System Verification is a global software quality assurance company specialized in advanced quality monitoring and analytics. By using best practice QA methods and AI insights, they help clients deliver great end-user experiences.

• 7+ years of hands-on development/automation experience with Python.
• 7+ years of deep experience with database technologies including writing complex SQL queries.
• 4+ years of practical experience with Robot Framework.
• 4+ years of experience with CI/CD tools (e.g., Jenkins) and 5+ years with Git.
• Strong working proficiency with Linux and Bash scripting.
• Proven experience with test management tools (qTest, Zephyr) and collaboration suites (Jira, Bitbucket, Jenkins/Bamboo).
• Excellent analytical and problem-solving skills, with effective communication with Developers, Analysts, Product Owners, and Scrum Masters.
• Understanding of distributed data processing engines like Spark.
• Knowledge of the Hadoop ecosystem (Hive, Oozie, MapReduce, etc.).
• Basic knowledge of AWS architectural components (Lambda, Step Functions, State Machines, etc.).

Nice to have:

• Experience with containerization using Docker.
• Knowledge of streaming and message queue technologies (e.g., KAFKA, IBM MQ).
• Prior exposure to Scala/Spark.

Testing Strategy & Leadership:

• Defining test strategies, planning, and executing testing phases while identifying areas for process improvement.

Hands-on Automation:

• Designing and implementing robust test automation scripts and day-to-day automated solutions using Python and Robot Framework.

Requirement Analysis:

• Proactively analyzing and challenging project requirements when they lack clarity to ensure optimal delivery.

Test Management:

• Preparing test scenarios, managing test data, analyzing execution results, and reporting defects.

CI/CD Integration:

• Executing automated regression testing seamlessly through continuous integration pipelines.