Financial Data Platform Quality Automation

Context

Resume-backed QA Analyst and Support Engineer work on a multi-tenant financial data storage platform.

Problem

Manual regression and data checks were too slow for a platform handling ingestion, payment-data rules, transformations, and access-control behavior.

Role

Built test suites, API collections, data validation scripts, and Jenkins automation for regression evidence.

Constraints

• Financial data checks had to verify accuracy, consistency, and business rules.
• API coverage needed to replace a manual regression cycle.
• Failures had to point to ingestion, transformation, or access-control causes.

Approach

Built Python and Java suites for data and access-control validation, created Postman collections for REST endpoints, automated runs with Newman in Jenkins, and used MySQL/Pandas scripts for deeper data verification.

Challenges

The system required API and data checks to work together. A passing endpoint was not enough if transformations or business rules corrupted the output.

Impact

• Reduced manual testing effort by 80%.
• Developed 200+ Postman API collections for payment-data endpoints and business rules.
• Compressed Jenkins feedback from 3 hours to 25 minutes through pipeline streamlining and parallel execution.