Python Automation Test with Pyspark

Requirements:

1. Experience: A minimum of 6+ years of relevant experience in software testing and test automation, particularly using Python and Pyspark.

2. Python Proficiency: Strong programming skills in Python are essential, as automation testing in this role heavily relies on Python scripting.

3. Pyspark: Proficiency in Pyspark, which is a Python API for Apache Spark, is a key requirement. You should be skilled in using Pyspark for data processing and testing.

4. Automation Frameworks: Familiarity with test automation frameworks and tools such as Selenium, Appium, or others, depending on the specific application under test.

5. Testing Concepts: Solid understanding of software testing concepts, methodologies, and best practices, including test planning, test case design, and test execution.

6. SQL: Proficiency in SQL for database testing, especially when dealing with data using Pyspark.

7. Big Data: Experience or knowledge in working with Big Data technologies, data lakes, and distributed data processing is often valuable.

8. Data Testing: Experience in testing data pipelines, data transformations, and data quality using Pyspark.

9. Problem-Solving Skills: Strong analytical and problem-solving skills to identify and resolve issues during testing.

10. Communication: Effective communication skills to collaborate with development teams, stakeholders, and other team members.

11. Agile/Scrum: Familiarity with Agile methodologies, particularly Scrum, as many software development teams follow Agile practices.

12. Test Automation: Experience in test automation, including creating and maintaining automated test scripts and frameworks.

13. Test Documentation: Ability to create clear and comprehensive test documentation, including test plans, test cases, and test reports.

14. Continuous Integration: Experience with CI/CD (Continuous Integration/Continuous Deployment) practices and tools like Jenkins.

15. Linux/Unix: Familiarity with Linux/Unix environments as it's common in data processing and automation.

16. Version Control: Knowledge of version control systems like Git for code management.

17. Education: Typically, a bachelor's degree in a relevant field, such as Computer Science or Engineering, is required, but equivalent work experience may also be considered.