Automation Test Engineer

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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