QA Engineer - #2134817
Harnham - Data & Analytics Recruitment
Date: 1 hour ago
City: London
Salary:
£70,000
-
£75,000
/ year
Contract type: Full time
Work schedule: Full day
QA ENGINEER
LONDON/HYBRID
UP TO £75,000
This is an opportunity to join a growing technology business at a pivotal stage in its product journey. You will play a key role in shaping an AI-first approach to quality engineering, building scalable automation frameworks and helping deliver a high-quality web platform used in a data-intensive environment.
ROLES AND RESPONSIBILITIES:
The QA Engineer will:
- Design, develop, and maintain automated testing frameworks from the ground up.
- Create automated tests across front-end applications, APIs, and back-end systems.
- Validate complex data flows, ensuring accuracy, reliability, and data quality.
- Build regression testing capabilities to support ongoing platform enhancements and third-party integrations.
- Collaborate with developers, product teams, and stakeholders to improve testability and release quality.
- Drive the use of AI tooling within the testing lifecycle to increase efficiency and reduce manual effort.
- Support CI/CD processes and contribute to continuous quality practices.
- Help establish best practices for automation architecture, test coverage, and quality engineering.
YOUR SKILLS AND EXPERIENCE:
The ideal candidate will have the following skills and experience:
- Strong commercial experience with Java or Kotlin.
- Experience testing both frontend and backend systems.
- Hands-on API testing experience using tools such as Rest Assured, Postman, Swagger, or similar.
- UI automation experience with tools such as Selenium, Selenide, or Playwright.
- Understanding of JSON, XML, HTTP methods, response codes, and web architecture.
- Experience working with test frameworks such as JUnit or TestNG.
- Knowledge of SQL and data validation techniques.
- Experience with CI/CD pipelines and tools such as GitHub Actions.
- Familiarity with Jira, Confluence, or similar delivery tools.
- A strong interest in AI-native engineering practices, including the use of tools such as Claude and N8N to accelerate development, automation, and testing workflows.
- A mindset focused on removing manual effort through intelligent automation and process improvement.
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