Data Analyst
Actively Reviewing the ApplicationsLTM
Job Description
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
Required Skills
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