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- Tasks: Build scalable ETL pipelines and automate data updates for innovative projects.
- Company: Football Radar, a leader in data science based in Greater London.
- Benefits: Competitive salary, bonus scheme, extensive holidays, and health perks.
- Other info: Exciting opportunities for growth in a fast-paced environment.
- Why this job: Join a dynamic team and make an impact in the world of sports data.
- Qualifications: Solid Python and SQL skills; AWS familiarity is a plus.
The predicted salary is between 50000 - 65000 £ per year.
Football Radar in Greater London is seeking a Data Engineer to support its innovative data science efforts. You'll take ownership of data pipelines, ensuring that data is accurate and accessible.
Responsibilities include:
- Automating data updates
- Building datasets
- Deploying models to the cloud
Ideal candidates should have solid Python and SQL skills, and familiarity with AWS is preferred. The position offers competitive benefits including a bonus scheme, extensive holidays, and health and wellness perks.
Cloud Data Engineer - Build scalable ETL pipelines in London employer: Football Radar
Contact Detail:
Football Radar Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Cloud Data Engineer - Build scalable ETL pipelines in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Football Radar. A friendly chat can sometimes lead to opportunities that aren’t even advertised.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your ETL pipelines and any projects you've worked on. This gives you a chance to demonstrate your Python and SQL prowess in a tangible way.
✨Tip Number 3
Prepare for the interview by brushing up on AWS and data pipeline concepts. We recommend practising common interview questions and maybe even doing mock interviews with friends or mentors.
✨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, we love seeing candidates who take that extra step!
We think you need these skills to ace Cloud Data Engineer - Build scalable ETL pipelines in London
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your Python and SQL skills in your application. We want to see how you’ve used these tools in real projects, so don’t hold back on the details!
Tailor Your Application: Take a moment to customise your application for the Cloud Data Engineer role. Mention your experience with ETL pipelines and any work you've done with AWS to show us you're the perfect fit.
Be Clear and Concise: When writing your application, keep it clear and to the point. We appreciate straightforward communication, so avoid jargon and make your experience easy to understand.
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. We can’t wait to hear from you!
How to prepare for a job interview at Football Radar
✨Know Your Tech Inside Out
Make sure you brush up on your Python and SQL skills before the interview. Be ready to discuss specific projects where you've built ETL pipelines or worked with data automation. This will show that you not only understand the theory but have practical experience too.
✨Familiarise Yourself with AWS
Since familiarity with AWS is preferred, take some time to learn about the services relevant to data engineering, like S3, Lambda, and Redshift. Being able to talk about how you've used these tools or how you would use them in the role can really set you apart.
✨Prepare for Scenario-Based Questions
Expect questions that ask you to solve real-world problems related to data accuracy and accessibility. Think of examples from your past work where you had to troubleshoot data issues or optimise a pipeline, and be ready to explain your thought process.
✨Show Enthusiasm for Data Science
Football Radar is all about innovative data science efforts, so make sure to express your passion for the field. Share any personal projects or interests related to data science that demonstrate your commitment and excitement for the role.