Find a job 
Featured Companies 
Featured Universities 
For Companies 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 innovative data solutions.
- Benefits: Competitive salary, substantial bonuses, flexible hybrid/remote work options.
- Other info: Dynamic environment with opportunities for career growth and collaboration with top analysts.
- 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 relational databases.
The predicted salary is between 34000 - 46000 £ per year.
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.
The key responsibilities will include:
- 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, CloudFormation, Lambdas, CloudWatch) to support analytics infrastructure.
- Contribute to the development of dashboards and self-service analytics tools.
Qualifications
Essential:
- 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 optimize 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.
Desirable:
- Experience with BI tools (e.g., Power BI, Plotly/Dash) for visualization.
- Experience in frontend development – React/Javascript.
- Experience in structuring APIs – Django, Flask, FastAPI.
- 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.
- Side projects demonstrating end-to-end analytics solution design.
Junior Data Engineer in London employer: OTA Recruitment
Contact Detail:
OTA Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Junior Data Engineer in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving SQL, Python, and data modelling. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common data engineering questions and practical tasks. Practice explaining your thought process clearly, as communication is key when collaborating with analysts and stakeholders.
✨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 love seeing candidates who are genuinely interested in joining our team.
We think you need these skills to ace Junior Data Engineer in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the role of Junior Data Engineer. Highlight your SQL and Python skills, and any experience with data modelling or cloud services. We want to see how your background fits into our world of sports analytics!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data engineering and how you can contribute to our team. Don’t forget to mention any relevant projects or experiences that showcase your skills.
Showcase Your Projects: If you've worked on any side projects or have experience with BI tools, make sure to include them in your application. We love seeing practical examples of your work, especially if they demonstrate your problem-solving skills and creativity!
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and we’ll be able to review your application more efficiently. Plus, it shows us you’re keen to join our team!
How to prepare for a job interview at OTA Recruitment
✨Know Your Data Models
Make sure you brush up on data modelling concepts like star schema and dimensional modelling. Be ready to discuss how you've applied these in your previous work or projects, as this will show your understanding of the role's requirements.
✨SQL and Python Proficiency
Since SQL and Python are essential for this position, practice writing queries and transforming data using Python. You might be asked to solve a problem on the spot, so being comfortable with these languages will give you a significant edge.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've debugged slow queries or optimised workflows in the past. This is a key part of the job, and demonstrating your analytical mindset will impress the interviewers.
✨Familiarity with Cloud Tools
Get familiar with cloud-based tools like AWS S3 and Athena. If you have experience with these platforms, be sure to highlight it. Even if you don’t, showing enthusiasm for learning about them can go a long way!