Senior Quality Engineer

Quality Engineering & Test Strategy
• Understand business requirements, existing legacy application behavior, and the target modernized architecture.
• Develop comprehensive test strategies covering functional, integration, API, end-to-end, regression, and data validation.
• Identify critical business journeys and create risk-based testing approaches.
• Ensure functional parity between the legacy and modernized applications.
• Define traceability between business requirements, test scenarios, test cases, automation, and defects.
• Work closely with product owners, business analysts, developers, architects, and DevOps teams.

Functional & End-to-End Testing
• Design and execute functional test scenarios for applications built using Angular and .NET.
• Validate complex end-to-end business workflows across multiple applications and integrations.
• Perform system integration testing across APIs, applications, databases, third-party platforms, and downstream systems.
• Design regression suites based on business criticality and change impact.
• Identify opportunities for automation and continuous regression.
API & Integration Testing
• Perform functional and integration testing of REST APIs and backend services.
• Validate API contracts, request/response structures, business rules, authentication, error handling, and downstream integrations.
• Build automated API validation suites using appropriate tools and frameworks.
• Validate integration flows across AWS services and enterprise systems.
Database Migration & ETL Testing
• Validate migration of data from SQL Server to PostgreSQL.
• Perform source-to-target data reconciliation and transformation validation.
• Validate:
    o Record counts and completeness
    o Data accuracy and integrity
    o Data types and schema mappings
    o Transformation rules
    o Referential integrity
    o Duplicate and missing records
    o Null handling
    o Stored procedures and database logic
    o Historical and incremental data loads
    
• Write complex SQL queries for data validation and reconciliation.
• Identify data anomalies introduced during migration or transformation.
• Develop reusable automated data validation and reconciliation utilities.