Python Coding
3 days ago
Responsibilities:
Develop & Maintain Test Automation Frameworks: Design and implement test automation
frameworks using Python, ensuring robustness, scalability, and maintainability.
Test Tool Development: Build custom tools and utilities for enhancing the testing process,
leveraging Python and other relevant technologies.
SDET Expertise: Work closely with the development team to write efficient, reusable test code
that integrates seamlessly into the CI/CD pipeline.
Test Planning & Execution: Develop and execute comprehensive test plans, including
functional, regression, performance, and integration tests.
Collaboration: Work in close collaboration with development, product, and operations teams to
understand software requirements and design appropriate testing strategies.
Automation Optimization: Continuously improve existing test scripts, tools, and processes to
increase efficiency, reduce maintenance, and optimize test execution time.
Analytical & Problem-Solving: Use strong analytical skills to identify areas of improvement,
troubleshoot issues, and provide solutions.
Continuous Improvement: Contribute to process improvements, best practices, and the
adoption of new technologies that enhance testing capabilities.
Documentation: Maintain clear and thorough documentation of testing processes, tools, and
frameworks.
Metrics and Reporting: Generate reports on testing metrics, providing insights into the quality
of the product and areas for improvement.
Qualifications:
5+ years of experience in software testing, including significant experience as an SDET or in a
similar role.
Strong experience with Python: Hands-on experience developing and maintaining test
automation frameworks, writing test scripts, and creating custom tools using Python.
Proficient in Automation Tools: Experience with popular automation tools and frameworks like
Selenium, PyTest, Robot Framework, or similar.
Familiarity with Python Libraries: Strong experience with Python libraries such as Pandas,
NumPy, Matplotlib, or SciPy for data manipulation, analysis, and visualization, especially for
reporting and logging purposes in automated test cases.
Strong Analytical Skills: Proven ability to analyze complex systems, diagnose issues, and
identify root causes.
Experience with CI/CD Pipelines: Familiarity with CI/CD tools such as Jenkins, GitHub, or
similar.
Knowledge of Testing Methodologies: In-depth understanding of testing methodologies, test
levels, and test strategies (unit, integration, functional, performance, etc.).
Database Testing & SQL: Experience with testing database-driven applications and writing SQL
queries to validate data.
Version Control: Familiarity with version control tools like Git.
Problem-Solving Mindset: Strong troubleshooting and problem-solving abilities in complex
systems and tools.
Communication Skills: Strong verbal and written communication skills, with the ability to
explain technical concepts clearly.
Preferred Skills (Nice to Have):
AI/ML Knowledge: Understanding of artificial intelligence (AI) and machine learning (ML)
concepts, frameworks, and libraries like TensorFlow, PyTorch, or Scikit-learn.
GenAI Expertise: Familiarity with Generative AI (GenAI) technologies, such as GPT or similar
models, and their application in automating or enhancing testing and development processes.
OCR Technology: Experience with Optical Character Recognition (OCR) technology, tools, and
frameworks like Tesseract or Google Vision API, particularly in testing document processing or
image-based data systems.
Cloud Testing: Experience with testing in cloud-native environments (AWS, Azure, Google
Cloud).
Containerization: Familiarity with containerization technologies like Docker.
API Testing: Experience with API testing tools (e.g., Postman, REST Assured).
Performance Testing: Knowledge of performance testing tools like JMeter or LoadRunner.
Agile Methodologies: Exposure to Agile methodologies and working in Agile environments.
Test-Driven Development (TDD) or Behavior-Driven Development (BDD) experience.
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