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- Tasks: Support live sports data systems and build predictive analytics for real-time insights.
- Company: Join a leading sports analytics firm with a fully remote team.
- Benefits: Flexible work environment, competitive salary, and opportunities for professional growth.
- Why this job: Combine your passion for sports with cutting-edge data engineering to make an impact.
- Qualifications: BS/BA in a related field and 2+ years of coding experience in Python and SQL.
- Other info: Ideal for sports enthusiasts looking to innovate in the analytics space.
The predicted salary is between 45000 - 55000 £ per year.
A sports analytics firm is seeking a Data Engineer to join their fully remote team. The ideal candidate will have a BS/BA in a related field and over 2 years of experience in production-level coding, particularly in Python and SQL.
Responsibilities include:
- Supporting live sports data systems
- Architecting real-time analytics
- Building predictive products
A strong interest in sports, particularly Tennis, is essential, alongside skills in cloud computing, ETL processes, and machine learning concepts.
Real-Time Data Engineer — Remote, Sports Analytics in London employer: Swish Analytics
Contact Detail:
Swish Analytics Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Real-Time Data Engineer — Remote, Sports Analytics in London
✨Tip Number 1
Network like a pro! Reach out to folks in the sports analytics field on LinkedIn or join relevant online communities. We can’t stress enough how personal connections can open doors for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python, SQL, and real-time data systems. We love seeing practical examples of what you can do!
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and understanding the latest trends in sports analytics. We recommend practising common interview questions related to data engineering and machine learning.
✨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’re always on the lookout for passionate candidates who love sports as much as we do!
We think you need these skills to ace Real-Time Data Engineer — Remote, Sports Analytics in London
Some tips for your application 🫡
Show Your Passion for Sports: Make sure to highlight your love for sports, especially Tennis, in your application. We want to see that you’re not just a tech whiz but also someone who gets excited about the world of sports analytics!
Tailor Your Experience: When detailing your experience, focus on your production-level coding skills in Python and SQL. We’re looking for specific examples of how you've used these skills in real-time data systems or predictive products.
Highlight Relevant Skills: Don’t forget to mention your knowledge of cloud computing, ETL processes, and machine learning concepts. These are key areas for us, so make sure they shine through in your written application!
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 Swish Analytics
✨Know Your Tech Inside Out
Make sure you brush up on your Python and SQL skills before the interview. Be ready to discuss your past projects and how you've used these languages in production-level coding. It’s a good idea to prepare some examples of how you’ve tackled challenges in real-time data systems.
✨Show Your Passion for Sports
Since this role is in sports analytics, it’s crucial to demonstrate your enthusiasm for sports, especially Tennis. Share any relevant experiences or insights you have about the sport and how they relate to data analysis. This will show that you’re not just a tech whiz but also genuinely interested in the field.
✨Understand the Company’s Products
Take some time to research the company’s existing products and services. Familiarise yourself with their approach to real-time analytics and predictive products. Being able to discuss their work and how you can contribute will set you apart from other candidates.
✨Prepare for Technical Questions
Expect technical questions related to cloud computing, ETL processes, and machine learning concepts. Brush up on these topics and be prepared to explain how you’ve applied them in your previous roles. Practising coding problems or scenarios can also help you feel more confident.