Python Automation Test Engineer

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).
• 3 - 5 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).

(ref : hirist.tech)