
Python Automation Test Engineer
21 hours ago
Job Summary :
We are seeking a highly skilled Python Automation Engineer with strong expertise in data automation, statistical analysis, and software testing. The ideal candidate will have hands-on experience with Python (Pandas), Power BI, and a solid understanding of automation frameworks and testing methodologies. The role requires excellent analytical skills, attention to detail, and the ability to work collaboratively in an Agile environment.
- Design, develop, and maintain Python automation scripts for data validation, testing, and analysis.
- Utilize Pandas for data processing and transformation within automation workflows.
- Develop and execute test plans, test cases, and automation suites to ensure software quality.
- Perform data visualization and reporting using Power BI.
- Apply strong statistical and analytical techniques for test data evaluation.
- Collaborate with development, QA, and data teams to identify and resolve automation issues.
- Follow best practices in version control, CI/CD, and Agile processes.
- Maintain clear documentation of automation frameworks, scripts, and reports.
- Bachelors degree in Electrical Engineering or a related technical field (or equivalent work experience).
years of experience as a Python Automation Engineer or similar role.
- Strong exposure to Pandas for data manipulation and analysis.
- Solid understanding of statistical principles and data validation.
- Strong knowledge of software testing methodologies and QA best practices.
- Good programming/scripting skills in Python.
- Expertise in Power BI for visualization and dashboarding.
- Excellent analytical, problem-solving, and communication skills.
- Strong attention to detail and commitment to quality.
- Ability to work collaboratively within a team-oriented environment.
- Experience with test automation frameworks (BDD, Selenium WebDriver, Appium, TestNG).
- Knowledge of CI/CD pipelines and tools.
- Familiarity with Git or other version control systems.
- Experience with performance testing tools (JMeter, Gatling).
- Understanding of Agile development methodologies (Scrum, Kanban).
- Exposure to cloud-based ML platforms (AWS, Azure, Google Cloud).
- Knowledge of containerization and orchestration tools (Docker, Kubernetes).
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