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- Tasks: Support live sports data systems and build predictive analytics for real-time insights.
- Company: Join a dynamic sports analytics firm with a fully remote team.
- Benefits: Flexible remote work, 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: 2+ years in coding with Python and SQL; strong interest in sports, especially Tennis.
- Other info: Exciting projects in a fast-paced environment with room for innovation.
The predicted salary is between 36000 - 60000 £ 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 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
✨Tip Number 1
Network like a pro! Reach out to folks in the sports analytics field on LinkedIn or at industry events. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your Python and SQL projects, especially those related to real-time data or sports. This will give you an edge when chatting with potential employers.
✨Tip Number 3
Stay updated on the latest trends in sports analytics. Follow relevant blogs, podcasts, or webinars. Being knowledgeable about current developments can impress interviewers and show your passion for the field.
✨Tip Number 4
Apply through our website! We make it easy for you to showcase your skills and passion for sports analytics. Plus, it shows you're serious about joining our team!
We think you need these skills to ace Real-Time Data Engineer — Remote, Sports Analytics
Some tips for your application 🫡
Show Your Passion for Sports: When you're writing your application, let your love for sports shine through! Mention any relevant experiences or projects that highlight your interest in sports analytics, especially if you have a soft spot for Tennis.
Highlight Your Technical Skills: Make sure to showcase your coding skills in Python and SQL. We want to see how you've used these languages in real-world scenarios, so don’t hold back on sharing specific examples from your past work!
Tailor Your Application: Don’t just send a generic application. Take the time to tailor your CV and cover letter to match the job description. Highlight your experience with cloud computing, ETL processes, and machine learning concepts to show us you’re the perfect fit.
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 makes the process smoother for everyone involved!
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. They’ll likely want to see how you can apply your technical knowledge to real-time data systems.
✨Show Your Passion for Sports
Since this role is in sports analytics, it’s crucial to express 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 help you connect with the interviewers on a personal level.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills in real-time data scenarios. Think of examples where you’ve had to architect solutions or build predictive products. Practising these scenarios will help you articulate your thought process clearly during the interview.
✨Familiarise Yourself with Cloud Computing and ETL
Since cloud computing and ETL processes are part of the job, make sure you understand the basics and can discuss them confidently. Be prepared to talk about any tools or platforms you’ve used, and how they can be applied to support live sports data systems.