Quality Engineer IV

Financial Crimes Quality Engineer

Be part of a collaborative Financial Crimes Quality Engineering team responsible for ensuring the quality, accuracy, reliability, and performance of critical Financial Crimes applications and data. The Quality Engineer will partner with engineering, product, operations, and other technology teams to develop and execute comprehensive testing strategies supporting Anti-Money Laundering (AML), Customer Due Diligence (CDD), Currency Transaction Reporting (CTR), Sanctions, and other Financial Crimes capabilities.

This role requires hands-on experience across data quality testing, functional and user-interface testing, integration testing, regression testing, and test automation. The Quality Engineer will participate throughout the Agile delivery lifecycle and help establish reusable testing practices, automation, and quality standards across Financial Crimes technology.

Key Responsibilities

• 
  
• Develop and execute test strategies, test plans, test scenarios, and test cases based on business, technical, and regulatory requirements.
• 
  
• Perform functional, integration, regression, end-to-end, UI, API, and data testing for Financial Crimes applications.
• 
  
• Validate data throughout complex data pipelines, including source-to-target reconciliation, transformation logic, data completeness, accuracy, timeliness, duplication, and exception scenarios.
• 
  
• Use SQL extensively to validate data, investigate discrepancies, reconcile record counts, and confirm business and transformation rules.
• 
  
• Perform testing of upstream and downstream integrations to ensure data is processed accurately across Financial Crimes systems.
• 
  
• Develop, execute, and maintain automated test suites using Katalon and other approved automation technologies.
• 
  
• Use qTest to manage test cases, test execution, traceability, evidence, and defect tracking.
• 
  
• Partner with developers and data engineers to incorporate automated testing and quality checks into CI/CD and data-delivery pipelines.
• 
  
• Identify opportunities to automate repetitive functional, regression, data-validation, and integration tests.
• 
  
• Perform defect identification, documentation, triage, retesting, and root-cause analysis in partnership with engineering teams.
• 
  
• Support testing of data-quality controls and validation patterns, including record-count reconciliation, required-field and identifier validation, reference/lookup validation, duplicate detection, and abnormal data-volume detection. These patterns align directly with the Financial Crimes data-management work already underway.
• 
  
• Help shift quality earlier in the delivery lifecycle by validating data and application functionality before defects or poor-quality data reach downstream Financial Crimes platforms.
• 
  
• Work collaboratively within Agile delivery teams and participate in planning, refinement, daily stand-ups, retrospectives, demonstrations, and release activities.
• 
  
• Contribute to the broader Financial Crimes Quality Engineering strategy, including standards, reusable automation, testing practices, metrics, and continuous improvement.
• 
  

Preferred Experience / Technical Skills

• 
  
• Experience with quality engineering and software testing, including both manual and automated testing.
• 
  
• Strong SQL and data-testing skills, with experience validating large or complex datasets.
• 
  
• Experience testing ETL/ELT processes, databases, APIs, applications, and system integrations.
• 
  
• Hands-on experience with Katalon or comparable test-automation platforms.
• 
  
• Experience with qTest or similar test-management solutions.
• 
  
• Familiarity with Snowflake, DBT, Python, APIs, CI/CD pipelines, and modern data-engineering architectures is preferred.
• 
  
• Experience developing reusable automated tests and regression suites.
• 
  
• Strong understanding of Agile/Scrum delivery practices.
• 
  
• Ability to understand business requirements and translate them into comprehensive positive, negative, boundary, integration, and data-validation scenarios.
• 
  
• Strong analytical and troubleshooting skills with the ability to investigate complex application and data issues.
• 
  
• Strong communication and collaboration skills with the ability to partner across engineering, product, operations, and business teams.
• 
  
• Financial Services or Financial Crimes/AML experience is preferred, particularly experience supporting AML, CDD, CTR, Sanctions, transaction monitoring, or regulatory reporting systems.
•