At a Glance
- Tasks: Build scalable, AI-powered data applications and mentor fellow engineers.
- Company: Join Checkout.com, a leading tech company focused on innovation.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Dynamic team environment with excellent career advancement opportunities.
- Why this job: Make a real impact by shaping the future of data technology.
- Qualifications: Strong background in data systems and experience with stream processing technologies.
The predicted salary is between 70000 - 90000 £ per year.
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 are building for scale, so much of what we design and implement today is the technology infrastructure that 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, while 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.
Qualifications
- 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, primarily Kafka, but also Kinesis.
- 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, Python, Scala or C#.
Staff Data Platform Engineer employer: 0026 Checkout Technology Ltd
At Checkout.com, we pride ourselves on being an exceptional employer that fosters a culture of innovation and collaboration. Our Data and AI Platform Team is dedicated to empowering engineers with the tools and support they need to excel, while offering ample opportunities for professional growth and development in a dynamic environment. Located in a vibrant tech hub, we provide a unique chance to work on cutting-edge technologies that drive meaningful business solutions, all while enjoying a supportive and inclusive workplace.
Contact Details:
0026 Checkout Technology Ltd Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Staff Data Platform Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. 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 portfolio or GitHub repository showcasing your projects, especially those related to data streaming and AI. This gives potential employers a taste of what you can do beyond your CV.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice common interview questions, especially around event streaming technologies like Kafka and Flink, and be ready to discuss your past experiences.
✨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, it shows you’re genuinely interested in joining our team at Checkout.com.
We think you need these skills to ace Staff Data Platform Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Staff Data Platform Engineer role. Highlight your experience with stream processing technologies like Kafka and Flink, and showcase any relevant projects that demonstrate your skills in building scalable data applications.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about data engineering and how your background aligns with our mission at Checkout.com. Don’t forget to mention any leadership or mentoring experiences you've had!
Showcase Your Technical Skills:We want to see your technical prowess! Be sure to include specific examples of your hands-on experience with cloud technologies, container management, and CI/CD pipelines. This will help us understand how you can contribute to our team right away.
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about our culture and values.
How to prepare for a job interview at 0026 Checkout Technology Ltd
✨Know Your Tech Stack
Make sure you brush up on your knowledge of stream processing technologies like Kafka and Flink. Be ready to discuss your hands-on experience with these tools, as well as any cloud-based technologies you've worked with, such as AWS. Showing that you understand the tech stack will impress the interviewers.
✨Showcase Your Leadership Skills
Since this role involves mentoring and influencing others, prepare examples of how you've led teams or projects in the past. Think about times when you've built strong relationships with engineers and managers, and be ready to share those stories during the interview.
✨Prepare for Problem-Solving Questions
Expect questions that assess your problem-solving abilities, especially around event-driven use cases. Be prepared to discuss how you've approached challenges in previous roles, particularly those related to building scalable data applications or troubleshooting incident triage.
✨Communicate Clearly and Confidently
Strong presentation and communication skills are key for this position. Practice explaining complex technical concepts in a simple way, as if you're teaching someone new. This will not only help you during the interview but also demonstrate your ability to influence and mentor others.
