At a Glance
- Tasks: Design and optimise data models for sports analytics, transforming raw data into actionable insights.
- Company: Leading sports pricing provider with a focus on innovation and collaboration.
- Benefits: Competitive salary, substantial bonuses, flexible hybrid/remote work options.
- Other info: Dynamic environment with opportunities for growth and development in data engineering.
- Why this job: Join a pioneering team and make an impact in the exciting world of sports analytics.
- Qualifications: Proficient in SQL and Python, with experience in data modelling and cloud platforms.
The predicted salary is between 63000 - 77000 £ per year.
- Data Engineer - sports analytics/betting
- Salary £40k‑£55k (plus substantial bonus on top)
Location
- London or Leeds (very relaxed about hybrid/remote working)
- Company description
We are a proprietary sports pricing and product provider, specializing in the development of intricate, simulation‑driven pricing and risk systems that empower leading sports brands.
As pioneers in player‑level, play‑by‑play simulations and forecasting, we deliver the group’s most advanced pricing and risk capabilities – particularly focused on the US market.
Job Description
The purpose of the data engineer is to design, build, and optimize data models and analytics workflows that enable accurate, timely, and actionable insights across the business.
This role bridges the gap between data engineering and analytics, ensuring that data is transformed into well‑structured, reliable datasets for reporting, visualization, and advanced analytics.
The role holder will focus on creating scalable, maintainable solutions that empower stakeholders to make data‑driven decisions efficiently.
Key responsibilities
- Design and implement data models optimized for analytics and reporting use cases.
- Develop and maintain ELT/ETL pipelines to transform raw data into curated datasets.
- Collaborate with analysts and data scientists to understand requirements and deliver high‑quality data products.
- Optimize SQL queries and workflows for performance and scalability.
- Ensure data quality, consistency, and governance across all analytics layers.
- Implement best practices for documentation, testing, and reproducibility in analytics workflows.
- Work with cloud‑based tools and services (e. g., AWS S3, Athena, ECS, Cloud Formation, Lambdas, Cloud Watch) to support analytics infrastructure.
- Contribute to the development of dashboards and self‑service analytics tools.
Qualifications
- Competent in SQL and Python for data transformation and analytics.
- Understanding of data modelling concepts (e. g., star schema, dimensional modelling).
- Experience (1+ year) working with relational databases and designing optimized schemas.
- Ability to debug and optimise slow queries and inefficient workflows.
- Familiarity with cloud‑based data platforms and services (AWS preferred).
- Excellent communication skills for collaborating with technical and non‑technical stakeholders.
- Strong problem‑solving and analytical mindset.
- Experience with BI tools (e. g., Power BI, Plotly/Dash) for visualisation.
- Experience structuring APIs – Django, Flask, Fast API.
- Familiarity with distributed systems (e. g., Spark, Kafka) for large‑scale analytics.
- Knowledge of testing practices (e. g., TDD) in data workflows.
- Passion for clean, well‑documented systems and reproducibility.
Seniority level
Associate
Employment type
Full‑time
Job function
- Information Technology
- #J-18808-Ljbffr
Junior Data Engineer in England employer: OTA Recruitment
As a leading provider in sports analytics and betting, we offer an exceptional work environment that prioritises innovation and collaboration. Our flexible hybrid/remote working model allows for a healthy work-life balance, while our commitment to employee growth ensures that you will have ample opportunities to develop your skills and advance your career. Join us in London or Leeds, where you can be part of a dynamic team that is shaping the future of sports pricing and risk systems.
StudySmarter Expert Advice🤫
We think this is how you could land Junior Data Engineer in England
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like OTA Recruitment!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Junior Data Engineer at OTA Recruitment.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like OTA Recruitment.
✨Apply Directly through Our Website
When you find a suitable opening like Junior Data Engineer at OTA Recruitment, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Junior Data Engineer in England
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at OTA Recruitment, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at OTA Recruitment. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at OTA Recruitment
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at OTA Recruitment!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
