At a Glance
- Tasks: Join a dynamic team to ensure top-notch software quality for F1 racing applications.
- Company: Be part of an innovative tech company at the forefront of Formula 1 technology.
- Benefits: Enjoy flexible hours, competitive salary, bonuses, and health perks including private healthcare.
- Other info: Exciting career growth opportunities in a fast-paced, collaborative tech environment.
- Why this job: Make a real impact on performance in a high-stakes environment watched by millions.
- Qualifications: Extensive QA experience with strong programming skills, especially in C#.
The predicted salary is between 49500 - 60500 £ per year.
4 days onsite + 1 day remote (commutable from Northamptonshire / Buckinghamshire / Oxfordshire / Bedfordshire)
Permanent - basic salary DOE, championship & race weekend bonuses, flexible onsite hours (10am - 3pm), pension (5%), daily lunch allowance, life insurance (4x salary), private healthcare, onsite gym & EV charging.
2.62 seconds. The time it takes to service an entire F1 racing car at the pit stop.
In Formula 1, every line of code, tool, and application you help develop has a direct impact on performance on the track.
In a sport watched by over 525 million fans globally, even the smallest software gain can translate into meaningful lap time improvements.
You’ll be the third QA Engineer in a brand-new QA and Testing function, becoming an extra pillar in the Technology department, alongside Software Engineering, Platform Engineering, and Data Science.
What you’ll do
You’ll contribute to the overall QA vision, supporting the direction of the function while helping shape testing approaches that are tailored to the needs of the technology platforms.
This includes both manual and automated testing methods, ensuring software is robust, reliable, and race-ready.
You’ll test a range of software applications that support racing operations - including web-based tools, desktop applications, and APIs.
Most of these applications are developed in C#, and the QA process involves validating their performance, reliability, and correctness with tools like Postman & Selenium.
As systems become more complex and interdependent, the need for rigorous testing and seamless integration is critical.
By embedding quality assurance into the development lifecycle, you'll help reduce failure risk, increase velocity, and ultimately improve performance.
You’ll introduce and standardise testing methodologies, tools, and workflows across multiple development teams to ensure consistency and reliability.
You will plan and execute end-to-end testing across a diverse technology landscape, ensuring that all components, regardless of origin, function reliably and with high performance.
- What you’ll need
- Extensive QA experience across both manual and automated testing, ideally within integrated or complex systems.
- Proven experience in defining and implementing QA strategies, processes, and standards from the ground up.
- Hands-on knowledge of test automation tools and frameworks, and the ability to lead automation efforts alongside manual testing where required.
- Strong programming skills, ideally in . NET/C# (or comparable object-orientated language).
- Experience with CI/CD pipelines and the ability to implement QA processes that integrate smoothly into fast-paced development environments.
- Strong understanding of the SDLC, Agile methodologies, and how QA fits into modern development and deployment workflows.
- #J-18808-Ljbffr
Senior Quality Assurance Engineer in Northampton employer: Data Science Talent
As a Senior Quality Assurance Engineer in the heart of the Formula 1 industry, you'll be part of a dynamic team that thrives on innovation and excellence. With a strong focus on employee well-being, we offer flexible working hours, generous bonuses, and comprehensive benefits including private healthcare and an onsite gym. Our collaborative work culture fosters professional growth and encourages you to make a tangible impact on high-performance technology that captivates millions worldwide.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Quality Assurance Engineer in Northampton
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Data Science Talent or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Data Science Talent.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Data Science Talent.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Data Science Talent that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace Senior Quality Assurance Engineer in Northampton
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Data Science Talent.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Data Science Talent and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Data Science Talent
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Data Science Talent uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
