SDET

Key Responsibilities:

• Engaging in the planning and design process.
• Validate ETL and data workflows running on Azure Databricks for accuracy, performance, and reliability.
• Ensuring code reliability and robustness along with function specificity
• Design, develop, and maintain automated test frameworks for data pipelines, APIs, and containerized services.
• Build and execute integration, performance, and regression test suites for Flask-based APIs.
• Implement CI/CD quality gates in containerized deployments (Kubernetes).
• Collaborate with data engineers, software developers, and DevOps teams to identify test gaps and drive quality improvements.
• Monitor and troubleshoot test failures, ensuring timely resolution of defects.
• Contribute to best practices for testing in cloud-native and data-intensive environments.

Required Skills & Experience:

• Strong programming skills in Python, with proven experience writing test automation frameworks.
• Adept with white box testing.
• Hands-on experience testing data platforms (preferably Azure Databricks, Spark, or other big data frameworks).
• Experience with API testing (REST/Flask) using frameworks like PyTest, unittest, or similar.
• Proficiency in Kubernetes, Docker, and containerized environments.
• Familiarity with CI/CD tools (e.g., Azure DevOps, GitHub Actions, Jenkins).
• Strong knowledge of software testing principles including functional, regression, integration, and performance testing.
• Experience with SQL and validating large datasets.

Preferred Qualifications:

• Experience with cloud platforms, especially Azure (Databricks, Data Lake, Kubernetes Service).
• Exposure to data quality frameworks or libraries (e.g., Great Expectations).
• Knowledge of monitoring tools (Prometheus, Grafana, or similar) for validating system health and performance.
• Strong analytical and problem-solving skills with attention to detail.