At a Glance
- Tasks: Build and scale a cutting-edge data platform that powers analytics and AI.
- Company: Join a dynamic B2B SaaS company with ambitious growth plans.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional development.
- Other info: Exciting chance to work in a fast-paced environment with excellent career growth.
- Why this job: Make a real impact by shaping the future of data infrastructure.
- Qualifications: Strong Python skills and experience with AWS and Terraform required.
The predicted salary is between 60000 - 75000 £ per year.
A strong opportunity for an engineer who wants to build the data platform an entire organisation runs on, not just the pipelines on top of it. We're partnering with a well-backed B2B SaaS business whose software underpins millions of transactions a year. Several established products now sit under one platform, and the company is putting serious investment behind the data infrastructure that ties it all together. It's a business with genuine scale and stability but the pace and ambition of something far younger, and it's going through a period of real growth and change.
With a data engineering team already in place, the focus now is on building the platform layer beneath them: the foundation, tooling and reusable building blocks that let everyone else move data quickly and safely. The platform is already on a modern footing, so this is about extending what it can do rather than untangling what came before.
The Role
You'll help scale the Databricks lakehouse that powers analytics and AI across the business, stand up the infrastructure behind new data commercialisation products, and design the abstractions and templates that let other teams work with data consistently from ingestion through to access. It's a hands-on role with real ownership: you'll take work from design through to production and have a genuine say in how the platform and its engineering practices evolve.
What you'll be doing
- Scaling and supporting the data lakehouse, building new capability that serves analytics and AI use cases across the business
- Designing the blueprints, abstractions and reusable templates that let service and analytics teams handle data safely and consistently
- Building the infrastructure and logic behind new data commercialisation products, working with product and commercial teams to turn data into revenue
- Writing ETL and contributing to data modelling where the platform alone isn't enough, for both internal analytics and external-facing products
- Owning your work end to end, from first design through to deployment
- Helping shape engineering standards and better ways of working for the team's internal customers
What we're looking for
Essential
- Strong Python and a track record of building data infrastructure that other engineers and analysts depend on
- Hands-on AWS and Terraform, with infrastructure as code as your default way of working
- Experience building on a modern lakehouse or warehouse (Databricks ideally, though Snowflake or BigQuery travels well)
- Ingestion and transformation tooling such as Fivetran and dbt
- A platform mindset: you take as much pride in building the tools and paved roads other engineers rely on as you do in shipping your own pipelines
Nice to have
- Working knowledge of streaming systems such as Kafka, and a feel for the abstractions that make event-driven data easy for other teams to consume
- Solid SQL and a good sense for data modelling, even if neither is your daily focus
- Awareness of how data workloads run in production on ECS and Kubernetes
The Stack
- Core: Python and SQL
- Databricks, with lakehouse storage on S3
- AWS (EventBridge, Kinesis, Lambda, S3, EC2) with Terraform for infrastructure as code
- Supporting: dbt and Fivetran for transformation and ingestion
- Kafka for streaming
- ECS and Kubernetes for orchestration
Don't worry if you don't tick every box. If you've got a solid data engineering foundation and the appetite to build, we'd like to hear from you.
Data Platform Engineer in London employer: Xcede
Join a dynamic B2B SaaS company in London that is at the forefront of data innovation, where your contributions will directly impact millions of transactions. With a strong emphasis on employee growth and a collaborative work culture, you'll have the opportunity to shape the future of our data platform while enjoying the benefits of a hybrid work model. This is not just a job; it's a chance to be part of a rapidly evolving organisation that values your expertise and fosters a supportive environment for professional development.
StudySmarter Expert Advice🤫
We think this is how you could land Data Platform Engineer in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with current employees at the company you're eyeing. A friendly chat can sometimes lead to opportunities that aren't even advertised.
✨Tip Number 2
Show off your skills! If you’ve got a portfolio or GitHub with projects related to data engineering, make sure to share it. It’s a great way to demonstrate your hands-on experience and passion for building data platforms.
✨Tip Number 3
Prepare for the interview by brushing up on relevant technologies like Python, AWS, and Databricks. Be ready to discuss how you've used these tools in past projects and how you can contribute to scaling their data lakehouse.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love hearing from candidates who are genuinely excited about building data infrastructure.
We think you need these skills to ace Data Platform Engineer in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the Data Platform Engineer role. Highlight your Python expertise, AWS experience, and any work with data infrastructure. We want to see how you can contribute to our platform!
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're excited about building a data platform that supports analytics and AI. Share specific examples of your past projects and how they relate to what we’re doing at StudySmarter. This is your chance to shine!
Showcase Your Projects:If you've worked on relevant projects, whether in a professional or personal capacity, make sure to mention them. We love seeing hands-on experience, especially with tools like Databricks, Terraform, and Fivetran. It helps us understand your practical skills!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates. Plus, it shows us you’re keen to join the StudySmarter team!
How to prepare for a job interview at Xcede
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, especially Python, AWS, and Databricks. Brush up on your knowledge of ETL processes and data modelling, as these will likely come up during the interview.
✨Showcase Your Platform Mindset
Be prepared to discuss how you've built tools or infrastructure that other teams rely on. Share specific examples of how your work has enabled others to move data quickly and safely, highlighting your pride in building a solid foundation.
✨Prepare for Hands-On Questions
Expect practical questions or scenarios where you might need to demonstrate your problem-solving skills. Think about how you would approach scaling a data lakehouse or designing reusable templates, and be ready to walk through your thought process.
✨Cultural Fit and Growth Mindset
This company is experiencing growth and change, so express your enthusiasm for working in a dynamic environment. Share examples of how you've adapted to new challenges and contributed to team standards, showing that you're not just a techie but also a team player.
