QA Engineer (Financial Services)

KEY RESPONSIBILITIES

• Develop comprehensive test strategies and end-to-end test plans based on business and technical requirements.
• Design, execute, and maintain functional, integration, regression, system, and user acceptance testing.
• Build and maintain automated test suites to improve test coverage and delivery speed.
• Leverage AI-enabled testing tools to improve test design, execution, defect analysis, and quality insights.
• Partners with developers, product owners, infrastructure, and security teams to identify risks early and ensure quality is built into every release.
• Validate complex business workflows, data integrity, system integrations, and reporting accuracy.
• Analyze defects, identify root causes, and clearly communicate findings to technical and business stakeholders.
• Contribute to continuous improvement of QA processes, automation frameworks, and quality metrics.
• Support Agile delivery teams by participating in sprint planning, backlog refinement, and release activities.
• Mentor junior QA engineers and help establish quality engineering best practices.

QUALIFICATIONS

• Delivers high-quality software with measurable reductions in production defects.
• Continuously improves automation coverage and testing efficiency.
• Uses AI tools responsibly to increase productivity while maintaining engineering rigor.
• Partners effectively with engineering and business teams to proactively identify quality risks.
• Champions continuous improvement and helps evolve modern Quality Engineering practices across the organization.

Preferred Qualifications

• Excellent written and verbal communication skills.
• Strong analytical and critical thinking abilities.
• Demonstrated problem-solving and decision-making skills.
• Ability to manage multiple priorities in a fast-paced Agile environment.
• Self-motivated with a continuous learning mindset.
• Ability to lead quality efforts on medium to large initiatives.
• Experience mentoring or coordinating other QA engineers is a plus.

Technical Qualifications

• 5–8 years of experience in Quality Assurance or Quality Engineering.
• Experience creating test strategies, test plans, test cases, and quality reports.
• Strong experience with Agile delivery methodologies (Scrum, Kanban).
• Experience designing and maintaining automated test frameworks.
• Strong SQL skills with experience validating complex datasets.
• Experience testing enterprise applications, APIs, cloud platforms, and system integrations.
• Familiarity with CI/CD pipelines and DevOps practices.
• Experience with AI-assisted software development and testing tools (such as GitHub Copilot, Microsoft Copilot, ChatGPT Enterprise, or AI-enabled testing platforms) is highly desirable.
• Experience with modern automation frameworks such as:
• Playwright
• Selenium
• Cypress
• Postman/Newman
• REST Assured
• Python or Java
• Experience with test management platforms such as Azure DevOps Test Plans, Jira/Xray, Zephyr, or similar.
• Understanding software quality metrics, risk-based testing, and test automation best practices.
• Experience testing cloud-based, security, and infrastructure solutions is preferred.

Key Attributes

We are looking for someone who

• Has a strong analytical mindset and enjoys solving complex technical problems.
• Is adaptable and comfortable working across multiple technologies and business domains.
• Has a "can-do" attitude and takes ownership of delivering quality outcomes.
• Is naturally curious and enjoys learning new technologies, tools, and approaches.
• Thinks creatively about improving quality through automation and AI.
• Works collaboratively with both technical and non-technical stakeholders.
• Can balance attention to detail with the ability to see the broader business picture.

Domain Experience

• Experience working within Financial Services, Asset Management, Private Equity, or Capital Markets environments is preferred.
• Understanding investment data, fixed income, capital markets, or financial reporting is a plus.
• Experience validating complex business processes and data flows across enterprise systems.

Education

• Bachelor’s degree in Computer science, Information Systems, Engineering, or a related field, or equivalent practical experience.