- Define and implement comprehensive test strategies, quality standards, and testing processes.

- Lead integration, regression, UAT, and release testing activities.

- Validate migration outcomes, data quality, and data reconciliation results.

- Drive the test automation strategy and adoption of automation frameworks.

- Manage defect lifecycle, root cause analysis, and resolution tracking.

- Coordinate with development, business, data, and product teams to ensure release readiness.

- Mentor QA resources and establish testing best practices across teams.

- Ensure testing processes align with banking application requirements and quality standards.

Required Skills :

- Strong experience in Test Automation and QA processes.

- Hands-on experience in API Testing.

- Strong SQL skills for data validation and testing.

- Experience in Data Reconciliation Testing and migration validation.

- Strong experience in Integration Testing and Regression Testing.

- Experience coordinating UAT and Release Validation.

- Proficiency in Defect Management and Root Cause Analysis.

- Strong analytical, problem-solving, and stakeholder-management skills.

GenAI Skills :

- Hands-on experience with GenAI coding assistants such as Claude Code, GitHub Copilot, or similar tools for AI-assisted development.

- Strong prompt engineering skills with the ability to provide clear instructions and feedback to AI tools.

- Ability to critically review, validate, and test AI-generated code and content before implementation.

- Basic understanding of LLM concepts, including RAG, context windows, hallucinations, and responsible AI practices.

Preferred Skills :

- Experience with Databricks validation frameworks.

- Hands-on experience with PySpark testing.

- Knowledge of performance testing and performance validation.

- Experience working on banking applications and financial technology platforms.