Overview
We’re recruiting an Automation Test Engineer for a leading software company that develops advanced solutions for trading and risk management across global financial and energy markets.
This is a hybrid role, requiring 2-3 days per week onsite in central London.
This position would suit someone who is technically strong in automation and testing, but also confident working directly with customers in a consultative environment, helping them validate and trust complex data-driven systems.
What you’ll bring
We’re looking for a bright, proactive, and personable Automation Test Engineer with experience across as many of the following areas as possible:
Core experience
- Strong background in integration testing and API testing
- Solid database and SQL knowledge, with the ability to validate complex data sets
- Experience working with BDD frameworks such as Gherkin, Cucumber, or SpecFlow
- Comfortable working as a self-starter, able to take ownership and drive testing activity
- Confident communicating with customers and stakeholders, acting as a consultant alongside the company’s product
deep C# or .NET development experience is not essential for this role.
Technical environment (exposure rather than tick-box)
You may have experience or familiarity with some of the following:
- APIs & Web Technologies: RESTful APIs, HTTP, JSON
- Test & Dev Tools: Git, CI/CD pipelines, Agile (Scrum / Kanban), JIRA
- Operating Systems: Windows and/or Linux
Additional skills that will set you apart
- Understanding of trading or financial data, allowing you to reason about the data you’re testing
- Experience testing high-volume, high-complexity systems
- Strong attention to detail combined with a pragmatic, problem-solving mindset
- Ability to collaborate closely with developers, product teams, and customers
Industry background
Experience in the following sectors would be highly beneficial:
- Energy or Financial Trading (knowledge of platforms such as Endur, Allegro, or Findur is advantageous but not required)
- Regulated software environments
- Data-intensive or enterprise-scale systems
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