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- Tasks: Support live sports data systems and build innovative analytics products.
- Company: Join a dynamic startup revolutionising sports analytics and betting.
- Benefits: Fully remote work, competitive salary, and opportunities for growth.
- Why this job: Combine your passion for sports with cutting-edge technology in a fast-paced environment.
- Qualifications: Experience in Python, SQL, and a strong interest in sports analytics.
- Other info: Work with a collaborative team and tackle unique challenges in the industry.
The predicted salary is between 36000 - 60000 £ 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 are looking for team-oriented individuals with an authentic passion for accurate and predictive real-time data who can execute in a fast-paced, creative, and continually-evolving environment without sacrificing technical excellence. Our challenges are unique, so we hope you are comfortable in uncharted territory and passionate about building systems to support products across a variety of industries and consumer/enterprise clients.
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 U.S.-based sports including the NFL, NBA, MLB, NHL, College Football, College Basketball, and the ability to 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 employer: Swish Analytics
Contact Detail:
Swish Analytics Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer - EU
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Swish Analytics. A friendly chat can open doors that applications alone can't.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repo showcasing your projects, especially those involving Python, SQL, and real-time data systems. This gives us a taste of what you can do!
✨Tip Number 3
Prepare for the interview by brushing up on sports analytics and the specific technologies mentioned in the job description. We love candidates who can talk shop and show genuine passion for sports betting!
✨Tip Number 4
Don’t forget to apply through our website! Completing the application process fully is key to being considered for the role. We want to see your enthusiasm right from the start!
We think you need these skills to ace Data Engineer - EU
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 interest in the field.
Highlight Your Technical Skills: Make sure to clearly outline your technical expertise, especially in Python, SQL, and any experience with tools like Airflow and Kubernetes. We’re looking for candidates who can hit the ground running, so don’t be shy about showcasing your coding chops!
Tailor Your Application: Take a moment to customise your application for this specific role. Mention how your background in data engineering and your understanding of predictive analytics can contribute to our unique challenges. A tailored application shows us you’re genuinely interested!
Complete the Application Process: After clicking 'Apply Now', make sure you fully complete the application on the follow-up screen. It’s super important to follow through, as we won’t consider incomplete applications. We can’t wait to see what you bring to the table!
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, as these are crucial for the role. Be ready to discuss your experience with Airflow, Kubernetes, and building ETL pipelines. Practising coding challenges can help you feel more confident.
✨Show Your Passion for Sports
Since this role is all about sports analytics, demonstrate your genuine interest in sports and betting. Be prepared to talk about your favourite sports, especially Tennis, and how your knowledge can enhance your work with data.
✨Prepare for Real-Time Problem Solving
Expect questions that test your ability to handle live issues during sporting events. Think of examples from your past experiences where you triaged problems quickly and effectively, showcasing your ability to stay calm under pressure.
✨Understand the Company’s Vision
Familiarise yourself with Swish Analytics and their approach to predictive sports analytics. Being able to articulate how your skills align with their mission will show that you’re not just looking for any job, but that you’re genuinely interested in contributing to their goals.