Experience in Python language

Test PySpark based data pipelines ensuring data correctness completeness transformation accuracy and performance

Perform endtoend testing of data ingestion processing and output across batch and streaming jobs

Design and execute manual and automated test cases based on requirements and data flows

Apply strong testing fundamentals test case design test execution defect identification documentation and closure

Build and maintain test automation to validate data pipelines APIs and system integrations

Integrate quality checks into DevSecOps CICD pipelines enabling automated validations and early feedback

Promote reusability of test assets utilities frameworks and data validation components

Collaborate with developers data engineers and platform teams to address quality risks early ShiftLeft

Analyze test results and clearly document outcomes options problems risks and status for stakeholders

Apply a Quality Engineering mindset focused on defect prevention riskbased testing and continuous improvement

Primary Skills Mandatory

PySpark data pipeline testing

Test automation data API or backendfocused

Strong testing fundamentals and practices

DevSecOps practices and tools

CICD integration for testing

Quality Engineering mindset with focus on reusability scalability and prevention

Secondary Skills Good to Have

HQL SQL for data validation and analysis

Strong problem solving and analytical skills

Data analysis and data quality validation

Experience with big data tools ecosystems

Ability to work independently and selfsufficiently

Clear written communication for test summaries risks and recommendations

Work Time-2-11.30 PM

Domain Insurance

Data Analyst