qa engineer (auto) for lending products

Astra Tech is a technology company that develops lending and credit-based financial products.

• Design and execute test strategies for lending products, covering functional, API, integration, and end-to-end testing
• Test the full lending lifecycle, including loan applications, approvals, disbursements, repayments, and collections
• Develop and maintain scalable API automation frameworks using Python (pytest) or Java, and integrate automated tests into CI/CD pipelines
• Build automated regression suites for critical business workflows, edge cases, negative scenarios, and exception handling
• Validate backend microservices, transaction integrity, database consistency, asynchronous processing, and message-driven workflows
• Test risk decisioning systems, including credit eligibility, approval rules, credit limits, and risk policies
• Collaborate with Product, Risk, Engineering, and DevOps teams to identify quality risks and ensure reliable releases
• Investigate complex defects, perform root cause analysis, and improve test coverage and automation efficiency

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field
• 5+ Years of QA experience, with hands-on expertise in backend, API automation, and integration testing
• Mandatory experience testing lending or credit-based products, such as personal loans, consumer lending, BNPL, or other credit products
• Strong understanding of the end-to-end lending lifecycle
• Hands-on experience developing API automation frameworks using Python (pytest) or Java
• Strong SQL skills and experience with database validation and data reconciliation
• Good understanding of REST APIs, distributed microservices, and asynchronous messaging systems
• Experience integrating automated regression testing into CI/CD pipelines
• Strong analytical, debugging, and problem-solving skills
• Excellent spoken and written English, with the ability to work independently and collaboratively
• Будет плюсом: experience testing credit decision engines, credit scoring, eligibility rules, credit limits, risk policies, or risk-based pricing; familiarity with SAS Decision Manager or similar automated decisioning solutions; experience with decision rule validation, regression testing, and comparing legacy and new decision engines; experience using AI-assisted engineering tools such as Claude Code, Codex, Cursor, or GitHub Copilot for test automation, test case generation, and debugging; experience with performance and load testing tools such as JMeter, k6, or Gatling; experience testing high-volume, high-availability, and transaction-intensive backend systems

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