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- Tasks: Build scalable data processing applications using cutting-edge technologies like Kafka and Flink.
- Company: Leading fintech company in Greater London with a focus on innovation.
- Benefits: Hybrid work environment, growth opportunities, and competitive salary.
- Why this job: Join a dynamic team and lead engineering initiatives in the exciting world of fintech.
- Qualifications: Strong programming skills and experience with AWS, SQL, and Kubernetes.
The predicted salary is between 54000 - 84000 £ per year.
A leading fintech company in Greater London seeks a Staff Data Platform Engineer to build scalable data processing applications. The role includes working with technologies like Kafka and Flink, leading engineering initiatives, and mentoring teams.
Candidates should have strong programming skills and experience with AWS, SQL, and Kubernetes. This position offers growth opportunities and a hybrid work environment.
Staff Data Platform Engineer - Streaming & AI employer: Checkout Ltd
Contact Detail:
Checkout Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Staff Data Platform Engineer - Streaming & AI
✨Tip Number 1
Network like a pro! Reach out to folks in the fintech space, especially those working with data platforms. A friendly chat can open doors and give you insights that might just land you that Staff Data Platform Engineer role.
✨Tip Number 2
Show off your skills! If you've got experience with Kafka, Flink, or AWS, make sure to highlight that in conversations. Share examples of projects where you've used these technologies to solve real problems.
✨Tip Number 3
Prepare for technical interviews by brushing up on your programming skills. Practice coding challenges and be ready to discuss your thought process. We all know that strong programming skills are key for this role!
✨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 seeing candidates who take the initiative to connect directly with us.
We think you need these skills to ace Staff Data Platform Engineer - Streaming & AI
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your programming skills and experience with technologies like AWS, SQL, and Kubernetes. We want to see how you can bring your expertise to the table!
Tailor Your Application: Don’t just send a generic application! Take the time to tailor your CV and cover letter to reflect the specific requirements of the Staff Data Platform Engineer role. We love seeing candidates who take this extra step.
Be Clear and Concise: When writing your application, keep it clear and to the point. We appreciate well-structured applications that make it easy for us to see your qualifications and experiences at a glance.
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. Plus, it’s super easy!
How to prepare for a job interview at Checkout Ltd
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, like Kafka, Flink, AWS, SQL, and Kubernetes. Brush up on your programming skills and be ready to discuss how you've used these tools in past projects.
✨Showcase Leadership Experience
Since the role involves leading engineering initiatives and mentoring teams, prepare examples of when you've taken charge or guided others. Think about specific challenges you faced and how you overcame them while supporting your team.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving abilities in real-world scenarios. Practice articulating your thought process clearly, especially when it comes to building scalable data processing applications.
✨Ask Insightful Questions
At the end of the interview, have a few thoughtful questions ready about the company’s data strategy or team dynamics. This shows your genuine interest in the role and helps you gauge if the company culture aligns with your values.
