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- Tasks: Develop and scale backend services using Python and GCP, while optimising data pipelines.
- Company: Innovative LegalTech SaaS start-up with a mission-driven approach.
- Benefits: Up to £100,000 salary, equity, and fully remote work.
- Why this job: Join a high-trust team and influence technical decisions from day one.
- Qualifications: Deep experience in Python, product development, and data engineering.
- Other info: Enjoy professional development time to explore new AI tools and tech.
The predicted salary is between 72000 - 108000 £ per year.
Senior Software Engineer – Backend & Data | Fully Remote (UK)
Founding Engineer | Python | GCP | Terraform | Event-Based Systems | Data Pipelines
An innovative, mission-driven LegalTech SaaS start-up is looking for a Senior Product Engineer (Backend & Data) with deep experience in Python, Product development, and Data engineering.
Role Information:
- Salary: Up to £100,000 (DOE) + Equity
- Location: Fully remote (UK only)
- Stack: Python, TypeScript, GCP, Pub/Sub, SQL & NoSQL, IaC (Terraform), CI/CD (GitHub Actions), Observability tools, AI tooling
You’ll join a remote first, high-trust engineering team working with a modern, cloud-native stack – with real influence over technical decisions from day one. You’ll take technical ownership of the backend to ensure it’s robust, scalable, and ready for real customers, while adding new Data-driven features, optimising performance, and shaping the long-term Product roadmap.
While your focus will be backend systems in Python, you’ll also work across the stack, collaborate directly with users, and bring a strong Product mindset to every decision. This role is ideal for someone who thrives on turning early-stage ideas into scalable, market-ready Products backed by solid Data pipelines.
Senior Product Engineer – Highlights:
- Enhance and scale backend services in Python
- Architect event-driven solutions in GCP with Pub/Sub & Cloud Run
- Build and optimise Python code for high-performance backend systems
- Integrate APIs, enrich Data, and deliver robust, scalable Data pipelines
- Implement modern IaC practices for deployment and automation
- Leverage AI and tooling of your choice to boost workflow efficiency and deliver innovative Product features
- Autonomy & Ambiguity – discover, design, and build without micromanagement.
- Professional Development – dedicated time to explore new AI tools, Data engineering practices, and emerging tech to keep the Product ahead of the curve. They want engineers to be setup to stay on top in the new AI world.
Senior Software Engineer | Python | Fully Remote employer: Wilson Brown
Contact Detail:
Wilson Brown Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Software Engineer | Python | Fully Remote
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or through tech meetups. We all know that sometimes it’s not just what you know, but who you know that can help you land that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python and data engineering. We want to see your work in action, so make it easy for potential employers to see what you can do.
✨Tip Number 3
Prepare for the interview like it’s the Super Bowl! Research the company, understand their tech stack, and be ready to discuss how your experience aligns with their needs. We’re talking about real influence over technical decisions here, so show them you’re the right fit.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who take that extra step to connect with us directly.
We think you need these skills to ace Senior Software Engineer | Python | Fully Remote
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the job description. Highlight your Python expertise, experience with GCP, and any work you've done on data pipelines or event-driven systems. We want to see how you can contribute to our mission!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to tell us why you're passionate about this role and how your background aligns with our needs. Share specific examples of your past projects that demonstrate your ability to turn ideas into scalable products.
Showcase Your Projects: If you've worked on relevant projects, whether personal or professional, make sure to include them in your application. We love seeing real-world applications of your skills, especially in Python and data engineering. It gives us a glimpse of what you can bring to the table!
Apply Through Our Website: We encourage you to apply directly through our website for a smoother process. This way, we can ensure your application gets the attention it deserves. Plus, it’s the best way to stay updated on your application status!
How to prepare for a job interview at Wilson Brown
✨Know Your Tech Stack
Make sure you’re well-versed in Python, GCP, and Terraform. Brush up on your knowledge of event-driven systems and data pipelines, as these are crucial for the role. Be ready to discuss how you've used these technologies in past projects.
✨Showcase Your Product Mindset
This role requires a strong product focus, so think about how your technical decisions impact the end user. Prepare examples of how you've turned ideas into scalable products and how you’ve collaborated with users to enhance features.
✨Demonstrate Problem-Solving Skills
Expect to face some technical challenges during the interview. Practice explaining your thought process when tackling complex problems, especially in backend development. Use real-life scenarios to illustrate your approach to optimising performance and building robust systems.
✨Emphasise Autonomy and Innovation
The company values autonomy, so be prepared to discuss how you thrive in self-directed environments. Share experiences where you’ve taken ownership of projects and introduced innovative solutions, particularly in AI tooling or data engineering practices.