Job Summary
Serve as a Lead Quality Engineer with six to eight years of experience driving robust testing strategies for Pega based anti money laundering solutions and product lifecycle management workflows in a hybrid work model ensuring reliable delivery of day shift releases that safeguard financial integrity and operational excellence.
Responsibilities
- Design comprehensive test strategies for complex Pega based anti money laundering workflows to ensure accurate detection coverage and regulatory compliance across multiple financial products and services.
- Develop reusable automated test suites that validate end to end product lifecycle management processes to improve quality consistency and reduce regression effort for large scale enterprise implementations.
- Coordinate with business analysts and product owners to translate anti money laundering and product lifecycle requirements into clear test scenarios that accurately reflect real world transaction and investigation patterns.
- Execute functional integration and system tests for Pega applications focusing on rule configurations case flows and decision logic to prevent defects from reaching production environments.
- Implement robust test data management practices that simulate diverse customer risk profiles transaction behaviors and product configurations to enhance coverage and defect detection rates.
- Review user stories and acceptance criteria during backlog grooming sessions and provide quality risk assessments that influence prioritization and release readiness decisions.
- Create detailed defect reports with precise impact analysis and collaborate closely with developers to reproduce troubleshoot and resolve issues in a timely and transparent manner.
- Optimize test execution in the hybrid work model by using collaboration tools and repositories to keep test assets traceable up to business requirements and release documentation.
- Apply domain understanding of check processing when available to design specialized test conditions that validate clearing timelines exception handling and reconciliation outcomes.
- Monitor quality metrics such as defect density test coverage and escape rates and present data driven insights that guide continuous improvement across the delivery lifecycle.
- Enhance automation frameworks for user interface and application programming interface layers to shorten day shift execution windows and enable reliable continuous integration pipelines.
- Ensure adherence to organization wide quality standards and regulatory expectations for anti money laundering systems including documentation practices and audit ready evidence.
- Mentor junior quality engineers by sharing best practices in test design automation and defect analysis to build a strong quality culture within the delivery team.
Qualifications
- Demonstrate six to eight years of progressive experience in software quality engineering with consistent ownership of test strategy design execution and defect management for complex enterprise applications.
- Show proven hands on experience validating Pega based solutions including rulesets case management flows and integrations with upstream and downstream systems.
- Exhibit strong understanding of anti money laundering concepts such as customer risk scoring transaction monitoring alerts and investigations and apply this knowledge in test scenario design.
- Display practical experience testing product lifecycle management processes including product setup versioning retirement and related workflow or configuration changes.
- Utilize test automation tools and scripting approaches to build maintainable suites for regression smoke and integration testing that operate efficiently within a hybrid work environment.
- Communicate effectively with cross functional stakeholders including developers business partners and compliance teams to clarify requirements discuss risks and agree on quality outcomes.
- Bring exposure to check processing or retail banking operations as a valued domain addition enabling richer test coverage for payment clearing and exception scenarios.
- Adhere to quality assurance methodologies such as risk based testing and requirement traceability while continuously updating skills through relevant training and industry learning.
关于高知特 (Cognizant)
高知特(Cognizant)（纳斯达克代码：CTSH）作为一家AI Builder和相关技术服务提供商，致力于通过打造全栈AI解决方案，帮助企业将人工智能投资转化为实际价值。公司凭借深厚的行业经验、流程优化和工程技术专长，将企业独特的业务场景融入科技系统，赋能组织释放人才潜能，推动切实成果，并帮助全球企业在瞬息万变的环境中保持领先。如需了解更多详情，敬请访问 cognizant.ai 或关注@cognizant。
补充雇佣信息
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