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- Tasks: Solve large-scale data warehousing problems and deliver impactful data products.
- Company: Leading streaming service provider based in London.
- Benefits: Full-time position with a dynamic environment focused on innovation.
- Why this job: Join a team that leverages AWS technologies to make a real impact.
- Qualifications: Experience with big data technologies and software engineering best practices.
- Other info: Exciting opportunity for growth in a fast-paced industry.
The predicted salary is between 36000 - 60000 £ per year.
A leading streaming service provider based in London is seeking a Data Engineer to join their Prime Video Core Analytics team. The role involves solving large-scale data warehousing problems, leveraging AWS technologies, and delivering impactful data products. Ideal candidates will have experience with big data technologies and software engineering best practices. This full-time position offers the opportunity to work in a dynamic environment focused on innovation.
Data Engineer, Core Analytics & Tooling in London employer: Prime Video & Amazon MGM Studios
Contact Detail:
Prime Video & Amazon MGM Studios Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer, Core Analytics & Tooling in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those working at companies you’re eyeing. A friendly chat can open doors and give you insights that job descriptions just can’t.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving big data technologies and AWS. This is your chance to demonstrate what you can bring to the table beyond just a CV.
✨Tip Number 3
Prepare for interviews by brushing up on common data engineering challenges. Think about how you’d tackle large-scale data warehousing problems and be ready to discuss your thought process.
✨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 are proactive about their job search.
We think you need these skills to ace Data Engineer, Core Analytics & Tooling in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with big data technologies and AWS. 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 Data Engineer position and how you can contribute to our Core Analytics team. Keep it engaging and personal.
Showcase Your Problem-Solving Skills: In your application, give examples of how you've tackled large-scale data warehousing challenges in the past. We love seeing candidates who can think critically and innovate!
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 from our team!
How to prepare for a job interview at Prime Video & Amazon MGM Studios
✨Know Your Data Inside Out
Make sure you brush up on your knowledge of big data technologies and AWS. Be prepared to discuss specific projects where you've solved data warehousing problems, as this will show your practical experience and understanding of the tools.
✨Showcase Your Problem-Solving Skills
Think of examples where you've tackled complex data challenges. Use the STAR method (Situation, Task, Action, Result) to structure your answers, demonstrating how you approached the problem and what impact your solution had.
✨Familiarise Yourself with the Company
Research the streaming service provider and their Prime Video Core Analytics team. Understand their products and recent innovations. This will help you tailor your responses and show genuine interest in the role and the company.
✨Prepare Questions to Ask
Have a few insightful questions ready to ask at the end of the interview. This could be about their data strategy or how they measure the success of their data products. It shows you're engaged and thinking critically about the role.
