Amritaparna Pal

About Amritaparna Pal

Senior Quality Architect with 5.8 years of experience specialized in end-to-end (E2E) validation for high-complexity platforms.​Currently, leading a strategic technical migration: Transitioning a massive Snowflake data validation suite from Tricentis Data Integrity (DI) into a custom, high-performance Python-based testing framework. While maintaining the UI automation of Guidewire PolicyCenter using Tricentis Tosca, concurrently engineering Gen-AI test data generators and leveraging GitHub Copilot to optimize script development and reduce technical debt.​Career trajectory—from managing Mainframe databases to architecting cloud-native AI-augmented test suites—enables me to ensure data trust across the entire software development lifecycle (SDLC).​TECHNICAL STACKAutomation : Python (Pytest, SQLAlchemy, Pandas), Tricentis Tosca, Tosca DI, PostmanData & Cloud : Snowflake, AWS (Athena/S3), Azure, Mainframe (JCL/DB2)Domain : Guidewire PolicyCenter, Pet Insurance, Life SciencesAI / DevOps : GitHub Copilot, Gemini API, Azure DevOps, JIRA, GitCERTIFICATIONS​Standardization: ISTQB® Certified Tester Foundation Level (CTFL).​Tricentis Tosca: Product Consultant (AS1, AS2, TDS1, TDS2, AE1).​Tricentis Data Integrity: Product Consultant.Postman: API Fundamentals Student Expert.​Cloud: AWS Certified Cloud Practitioner, Microsoft Azure Fundamentals (AZ-900).

Experience

1. Associate - Projects

   Cognizant

   Jan 2025 — Present · Kolkata, IN

   Role : Senior Test AnalystResponsibilities :Hybrid Automation Architecture: Architected a dual-layer strategy for Guidewire PolicyCenter; utilizing Tricentis Tosca for UI-driven functional flows while engineering a programmatic backend validation layer in Python.​Data Framework Engineering: Developing a scalable Python testing framework (Pytest, SQLAlchemy, Pandas) to replace legacy Tosca DI suites, optimizing execution performance and CI/CD compatibility for Snowflake warehouses.​Cross-Layer Validation: Leveraging SQLAlchemy ORM and Pandas DataFrames to ensure 100% data consistency between Guidewire front-end policy creation and Snowflake backend storage.​AI-Augmented Velocity: Spearheading a Gen-AI Synthetic Test Data Generator to eliminate manual data dependencies and leveraging GitHub Copilot to drive code-base modularity and peer-review standards.Recognitions: Received CTS Cheers Awards for \"Dare to Innovate\" and delivering technical excellence in client-facing roles.

Education

• Maulana Abul Kalam Azad University of Technology, West Bengal formerly WBUT

  Bachelor of Technology - B.Tech, Electronics and Instrumentation Engineering

• Barasat Kalikrishna Girls' High School

  High School