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Data Engineer - sports analytics/betting

OTA Recruitment
London
2 days ago
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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 groups 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.

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