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- Tasks: Build a scalable event streaming platform using Kafka and Flink while mentoring fellow engineers.
- Company: Join Checkout.com, a leading tech company in the heart of Greater London.
- Benefits: Enjoy competitive salary, health benefits, and opportunities for professional growth.
- Other info: Be part of a dynamic team with exciting career advancement opportunities.
- Why this job: Make an impact on innovative projects and shape the future of streaming technology.
- Qualifications: Strong communication skills and experience in Java or Python required.
The predicted salary is between 70000 - 90000 £ per year.
Checkout.com is looking for an ambitious Staff Data Engineer in Greater London to join our Data and AI Platform Team. The successful candidate will work with technologies like Kafka and Flink to build a scalable event streaming platform to support various engineering teams.
Responsibilities include:
- Mentoring
- Implementing infrastructure for streaming applications
- Participating in strategic initiatives
Candidates should have strong communication skills, engineering experience, and proficiency in Java or Python.
Staff Software Engineer — Streaming Platform in London employer: Checkout.com
Contact Detail:
Checkout.com Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Staff Software Engineer — Streaming Platform in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those working at Checkout.com. A friendly chat can open doors and give you insights that might just land you an interview.
✨Tip Number 2
Show off your skills! If you've got projects or contributions related to Kafka, Flink, or any relevant tech, make sure to highlight them in conversations. We love seeing real-world applications of your expertise.
✨Tip Number 3
Prepare for technical chats! Brush up on your Java or Python skills and be ready to discuss how you've tackled challenges in past roles. We want to see your problem-solving prowess in action!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows us you’re genuinely interested in joining our team at Checkout.com.
We think you need these skills to ace Staff Software Engineer — Streaming Platform in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with technologies like Kafka and Flink. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re excited about the Staff Data Engineer position and how your background makes you a perfect fit for our team.
Show Off Your Communication Skills: Since strong communication is key for this role, make sure your application reflects that. Whether it’s in your CV or cover letter, clarity and professionalism will go a long way in impressing us.
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’re considered for the role without any hiccups!
How to prepare for a job interview at Checkout.com
✨Know Your Tech Stack
Make sure you’re well-versed in Kafka and Flink, as these are key technologies for the role. Brush up on your Java or Python skills too, and be ready to discuss how you've used these tools in past projects.
✨Showcase Your Mentoring Skills
Since mentoring is part of the job, think of examples where you've guided others. Be prepared to share how you approach mentoring and what strategies you use to help your team grow.
✨Communicate Clearly
Strong communication skills are a must. Practice explaining complex technical concepts in simple terms, as you may need to collaborate with various engineering teams who might not have the same technical background.
✨Prepare for Strategic Discussions
Familiarise yourself with the company’s strategic initiatives. Think about how your experience can contribute to these goals and be ready to discuss your ideas on building scalable streaming applications.