Data Engineer - sports analytics/betting

Data Engineer - sports analytics/betting

Salary £50k-£65k (plus very lucrative 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 this role is to implement and maintain data infrastructure that facilitates data-driven decision making, innovation and operational efficiency while ensuring that the data pipeline is secure, reliable, and scalable. The role holder will build and maintain high-performance data systems that are foundational to driving business growth and success. The successful candidate will have a strong grasp of modern data modelling practices, analytics tooling, and interactive dashboard development in Power BI and Plotly/Dash (or similar).

Key responsibilities

• Design and implement scalable data architectures and systems to support business intelligence and analytics needs.
• Develop, optimize, and maintain ETL pipelines for efficient data integration and transformation.
• Oversee data storage solutions, including backup and recovery strategies to ensure data integrity and availability.
• Write and manage SQL queries to extract, manipulate, and analyze data for reporting and decision-making.
• Implement robust data security and privacy protocols in compliance with relevant regulations and best practices.
• Collaborate with clients and end users to gather requirements, provide updates, and deliver tailored data solutions.

Qualifications

• Proficient in writing clean, efficient, and maintainable SQL and Python code, particularly for data transformation and analytics use cases.
• Understanding of data modelling concepts and be able to design data models that are optimised for different user cases.
• Familiarity with SQL and experience working with and designing relational databases.
• Experience implementing data pipelines that run on Kafka or equivalent distributed event store and stream-processing platforms.
• Ability to debug and optimize failing or slow data pipelines and queries.
• Systems integration experience: networking, data migrations, API integration and design.
• Enthusiasm for clean systems, including documentation, logging, and reproducibility.
• Experience working with AWS S3, Athena, ECS, Cloud Formation, Lambdas & Cloudwatch.
• Familiar with analytics tools such as Power BI, Plotly/Dash, or similar for building interactive and impactful visualizations.
• Passion for TDD.