At a Glance
- Tasks: Lead the development of a cutting-edge event streaming platform using Kafka and Flink.
- Company: Join Checkout.com, powering payments for global giants like eBay and Spotify.
- Benefits: Enjoy a hybrid work model, competitive salary, and opportunities for personal growth.
- Other info: Collaborative culture that values diversity and supports your career journey.
- Why this job: Make a real impact in fintech while working with innovative technologies.
- Qualifications: Strong background in data systems and experience with stream processing technologies.
The predicted salary is between 66150 - 80850 £ per year.
We’re Checkout.com. You might not know our name, but companies like eBay, Spotify, Klarna, Uber, and Sony do, because we’re behind many of the digital experiences you use every day. We are where the world checks out, enabling over 10 billion transactions yearly for more than one billion global shoppers. Whether you want to book a holiday, order food, renew a subscription, or check out online, there’s a good chance our tech powers the payments behind the scenes. Our platform helps the most ambitious businesses deliver effortless digital experiences, at scale.
If you want to do career-defining work, you’ve come to the right place. We move fast, think globally, and believe great teams are built by hiring exceptional people with conviction, curiosity, and the desire to make an impact. With 20 offices across six continents and London as our HQ, we’re shaping the future of fintech – and we’re just getting started.
Checkout.com is looking for an ambitious Staff Data Engineer to join our Data and AI Platform Team. Our team’s mission is to build a platform where you can create reliable, scalable, AI-powered streaming and batch data applications, and share data across Checkout.com to improve business performance. The Data and AI Platform team is here to ensure internal stakeholders can easily collect, store, process and utilise data to build AI use cases and data products aiming to solve business problems. Our focus is on maximising the amount of time engineers spend on solving business problems and minimising time spent on technical details around implementation, deployment, and monitoring of their solutions.
We're building for scale. As such, much of what we design and implement today is the technology/infrastructure which will serve hundreds of teams and petabyte-level volumes of data.
Key Responsibilities
- Work with stream processing technologies (Kafka and Flink) to build a continuously available large-scale event streaming platform.
- Leverage subject matter and technical expertise to provide leadership, mentoring, and strategic influence across the organisation whilst building strong relationships with engineers and engineering managers.
- Build tooling (modules/SDKs/DSLs) and associated documentation to foster the adoption of the streaming platform by enabling upstream teams and systems to easily publish data and deploy streaming applications.
- Implement all the necessary infrastructure to enable end users to build, host, monitor and deploy their own streaming applications.
- Provide consultancy across the technology organisation to drive the adoption of the platform and unlock event-driven use-cases.
- Participate, translate, run and execute the collection of requirements and architecture/design initiatives into action plans.
- Provide hands-on support for all event-based systems including incident triage and root cause analysis.
About You
While experience with our specific tech stack is a plus, we welcome candidates with a strong background in data systems who are eager to learn. The core remit of this role is to own and scale our event streaming capability, not to serve as a general DevOps or infrastructure engineer.
- Strong presentation and communication skills with a proven track record of influencing engineering organisations.
- Strong engineering background with a track record of implementing and owning event streaming platforms.
- Hands-on experience working with stream technologies, ideally Kafka.
- Experience designing and implementing stream processing applications with Flink.
- Experience working with cloud-based technologies such as AWS (MSK, S3, Lambda, ECS, SNS).
- Experience with Kubernetes (either self-hosted or on the cloud).
- Experience with SQL databases.
- Experience working with Docker, container deployment and management.
- Experience describing infrastructure as code (Terraform or similar) as well as designing and implementing CI/CD pipelines.
- Excellent programming skills with at least one of Java or Python.
Additional Information
We create the conditions for high performers to thrive, through real ownership, fewer blockers, and work that makes a difference from day one. Here, you’ll move fast, take on meaningful challenges, and be recognized for the impact you deliver. It’s a place where ambition gets met with opportunity, and where your growth is in your hands.
We work as one team, and we back each other to succeed. So whatever your background or identity, if you’re ready to grow and make a difference, you’ll be right at home here.
It’s important we set you up for success and make our process as accessible as possible. So let us know in your application, or tell your recruiter directly, if you need anything to make your experience or working environment more comfortable.
We understand that work is just one part of your life. Our hybrid working model offers flexibility, with three days per week in the office to support collaboration and connection.
Staff Data Engineer - Streaming Platform Lead (Hybrid) employer: Checkout Ltd
At Checkout.com, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. Our London headquarters is not just a workplace; it's a hub for career-defining opportunities where employees are empowered to take ownership of their projects and drive meaningful change. With a strong focus on personal growth, flexible hybrid working arrangements, and a commitment to inclusivity, we ensure that every team member can thrive and make a significant impact in the fintech landscape.
StudySmarter Expert Advice🤫
We think this is how you could land Staff Data Engineer - Streaming Platform Lead (Hybrid)
✨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 Checkout Ltd 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 Checkout Ltd.
✨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 Checkout Ltd.
✨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 Checkout Ltd 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 Staff Data Engineer - Streaming Platform Lead (Hybrid)
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 Checkout Ltd.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Checkout Ltd 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 Checkout Ltd
✨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 Checkout Ltd 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.