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- Tasks: Build cutting-edge data products and support real-time analytics for sports.
- Company: Join a dynamic startup revolutionising sports analytics and betting.
- Benefits: Remote work, competitive salary, and opportunities for professional growth.
- Why this job: Make an impact in the exciting world of sports data and analytics.
- Qualifications: Experience in Python, SQL, and a passion for sports is essential.
- Other info: Be part of a creative team in a fast-paced, evolving environment.
The predicted salary is between 50000 - 70000 £ per year.
Swish Analytics is a sports analytics, betting and fantasy startup building the next generation of predictive sports analytics data products. We believe that oddsmaking is a challenge rooted in engineering, mathematics, and sports betting expertise; not intuition. We deliver odds origination, risk management & trading software for the core four U.S. sports.
The Swish Analytics team is seeking Data Engineers based in Europe to have a direct impact on the infrastructure and delivery of our core consumer and enterprise data offerings as well as helping support our coverage of non-US sports. We’re a team passionate about accurate predictions and real-time data, and hope you find satisfaction in building new products with the latest and greatest technologies. This is a remote position.
Duties- Support production systems and help triage issues during live sporting events
- Architect low-latency, real-time analytics systems including raw data collection, feature development and endpoint production
- Build new sports betting data products and predictions offerings
- Integrate large and complex real-time datasets into new consumer and enterprise products
- Develop production-level predictive analytics into enterprise-grade APIs
- Contribute to the design and implementation of new, fully-automated sports data delivery frameworks
- BS/BA degree in Mathematics, Computer Science, or related STEM field
- Minimum of 2+ years of demonstrated experience writing production level code (Python)
- Proficiency in Python and SQL (preferably MySQL)
- Demonstrated experience with Airflow
- Demonstrated experience with Kubernetes
- Experience building end-to-end ETL pipelines
- Experience utilizing REST APIs
- Experience with version control (git), continuous integration and deployment, shell scripting, and cloud-computing infrastructures (AWS)
- Experience with web scraping and cleaning unstructured data
- Knowledge of data science and machine learning concepts
- A strong interest for sports and sports betting, with an emphasis on Tennis. An understanding of US-based sports including the NFL, NBA, MLB, NHL, College Football, College Basketball, and the ability use your knowledge of the sport to inform your work with complex datasets
Swish Analytics is an Equal Opportunity Employer. All candidates who meet the qualifications will be considered without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, pregnancy status, genetic, military, veteran status, marital status, or any other characteristic protected by law. The position responsibilities are not limited to the responsibilities outlined above and are subject to change. At the employer’s discretion, this position may require successful completion of background and reference checks.
Data Engineer - EU in London employer: Swish Analytics
Contact Detail:
Swish Analytics Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer - EU in London
✨Network Like a Pro
Get out there and connect with folks in the industry! Attend meetups, webinars, or even online forums related to data engineering and sports analytics. You never know who might have a lead on your dream job!
✨Show Off Your Skills
Create a portfolio showcasing your projects, especially those involving Python, SQL, and real-time data systems. Share it on platforms like GitHub and make sure it's easy for potential employers to see what you can do!
✨Ace the Interview
Prepare for technical interviews by brushing up on your coding skills and understanding of data pipelines. Practice common interview questions and be ready to discuss your past experiences and how they relate to the role at Swish Analytics.
✨Apply Through Our Website
Don't forget to apply directly through our website! It shows you're genuinely interested in joining the Swish Analytics team and makes it easier for us to find your application among the rest.
We think you need these skills to ace Data Engineer - EU in London
Some tips for your application 🫡
Show Your Passion for Sports: When you're writing your application, let your love for sports and sports betting shine through! We want to see how your enthusiasm aligns with our mission at Swish Analytics. Share any relevant experiences or projects that highlight your passion.
Highlight Your Technical Skills: Make sure to showcase your technical expertise in Python, SQL, and any other relevant tools. We’re looking for someone who can hit the ground running, so don’t hold back on detailing your experience with ETL pipelines, Kubernetes, and real-time analytics systems.
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 Data Engineer role. Mention how your skills and experiences make you a perfect fit for our unique challenges.
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 it gets into the right hands. Plus, it shows you’re serious about joining our team!
How to prepare for a job interview at Swish Analytics
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, especially Python, SQL, and Airflow. Brush up on your knowledge of Kubernetes and AWS too, as these are crucial for the role. Being able to discuss your experience with these tools confidently will show that you're ready to hit the ground running.
✨Show Your Passion for Sports
Since Swish Analytics is all about sports analytics, it’s essential to convey your genuine interest in sports and sports betting. Be prepared to discuss your favourite sports, teams, or even recent games. This will help you connect with the interviewers and demonstrate that you understand the industry.
✨Prepare for Real-Time Problem Solving
Given the fast-paced nature of the role, think of examples where you've had to troubleshoot issues under pressure. Whether it was during a live event or a tight deadline, showcasing your ability to remain calm and effective will impress the interviewers. They want to see how you handle challenges in real-time.
✨Ask Insightful Questions
Interviews are a two-way street, so come armed with questions that show your interest in the company and its products. Ask about their current projects, the team dynamics, or how they approach building predictive models. This not only shows your enthusiasm but also helps you gauge if the company is the right fit for you.