At a Glance
- Tasks: Build high-performance computational pipelines and optimise large datasets using Python.
- Company: Join a growing team developing an award-winning SaaS analytics platform.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Other info: Dynamic environment with a focus on innovation and collaboration.
- Why this job: Make a real impact in the insurance industry with cutting-edge technology.
- Qualifications: Strong Python skills and experience with large dataset management required.
The predicted salary is between 60000 - 80000 € per year.
Interested in being part of a growing, specialised team developing an award-winning SaaS analytics platform used to assess over £200bn of non-life insurance business? This is a mid to senior level software engineering role focused heavily on production-grade Python development. This is not a web-facing CRUD or API-endpoint development role. The core focus of this position is building high-performance computational pipelines, optimising memory for large datasets, and engineering mathematical/analytical engines. You will need relevant experience in this space to be considered. This is a hybrid role based in London (2 days per week in office).
The role:
- Technical Challenge: Take ownership of performance bottlenecks involving 4GB+ datasets.
- Architectural Input: Taking new features from conception to deployment.
- Production-Grade Python: Apply software engineering best practices including OOP, unit testing, and CI/CD.
- Mathematical/Financial Logic: Translating complex analytical, mathematical, or financial logic into reusable, production-grade software tools.
What We Are Looking For:
- Production-Grade Python: Strong experience writing clean, modular, and maintainable Python code (classes/functions, separation of concerns) within a professional software engineering environment.
- Large Dataset Management: Proven track record of preventing memory overheads and optimising execution speeds when manipulating massive (GB-scale) datasets, focusing on performance bottlenecks via vectorisation, parallelism, chunking, or memory optimisation.
- Analytical Pipelines: Experience building end-to-end analytical pipelines (data ingestion → computational transformation → modelling → output) rather than one-off analyses.
- Cloud Environments: Hands-on exposure to deploying and managing applications within a cloud environment (AWS, GCP, or Azure) and an understanding of how components fit together (API → compute → storage).
Backend Software Engineer (Python) in London employer: The Emerald Group Ltd, Search and Selection
Join a dynamic and innovative team in London, where you'll have the opportunity to work on cutting-edge SaaS analytics solutions that are transforming the non-life insurance industry. Our collaborative work culture fosters continuous learning and professional growth, with a strong emphasis on technical excellence and ownership of projects. Enjoy the flexibility of a hybrid working model while contributing to impactful projects that assess over £200bn in business.
Contact Detail:
The Emerald Group Ltd, Search and Selection Recruiting Team
StudySmarter Expert Advice🤫
We think this is how you could land Backend Software Engineer (Python) in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, or join online forums. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a GitHub repository showcasing your Python projects, especially those involving large datasets or analytical pipelines. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for technical interviews by brushing up on your problem-solving skills. Practice coding challenges that focus on performance optimisation and handling large datasets. We recommend platforms like LeetCode or HackerRank.
✨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 are proactive about their job search!
We think you need these skills to ace Backend Software Engineer (Python) in London
Some tips for your application 🫡
Show Off Your Python Skills:Make sure to highlight your experience with production-grade Python development. We want to see examples of clean, modular code you've written, so don’t hold back on showcasing your best work!
Talk About Big Data:Since we’re dealing with massive datasets, share your experiences managing and optimising large data. Discuss any performance bottlenecks you’ve tackled and how you’ve improved execution speeds – this is key for us!
Highlight Your Analytical Pipeline Experience:We love seeing candidates who have built end-to-end analytical pipelines. Make sure to detail your process from data ingestion to output, as this shows us you understand the full picture and can contribute effectively.
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to keep track of your application and ensure it gets the attention it deserves. We can’t wait to see what you bring to the table!
How to prepare for a job interview at The Emerald Group Ltd, Search and Selection
✨Know Your Python Inside Out
Make sure you brush up on your Python skills, especially around production-grade practices. Be ready to discuss OOP principles, unit testing, and CI/CD processes. They’ll likely want to see how you write clean, modular code, so have some examples from your past work at the ready.
✨Showcase Your Data Management Skills
Prepare to talk about your experience with large datasets. Think of specific instances where you’ve optimised memory usage or tackled performance bottlenecks. They’ll be keen to hear about your strategies for vectorisation, parallelism, and chunking, so have those examples handy.
✨Demonstrate Your Analytical Pipeline Experience
Be ready to explain how you've built end-to-end analytical pipelines in the past. They’ll want to know about your approach to data ingestion, transformation, modelling, and output. Highlight any projects where you’ve successfully managed these processes, as it shows you understand the full lifecycle.
✨Familiarise Yourself with Cloud Environments
Since this role involves cloud deployment, make sure you’re comfortable discussing your experience with AWS, GCP, or Azure. Understand how different components fit together, like APIs, compute, and storage. Being able to articulate your hands-on experience will set you apart.
