Data Engineer

Qualifications

Essential:   

• 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 (2+ year) working with and designing relational databases. 
• Experience (1+ year) 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 (1+ years): networking, data migrations, API integration and design. 
• Enthusiasm for clean systems, including documentation, logging, and reproducibility. 
• Experience (2+ year) working with AWS S3, Athena, ECS, Cloud Formation, Lambdas & Cloudwatch. 
• Excellent presentation, documentation, time management, communication skills with the ability to work collaboratively and autonomously. 
• Strong problem-solving skills with a pragmatic and analytical outlook.

Desirable:   

• Familiar with analytics tools such as Power BI, Apache Superset, or similar for building interactive and impactful visualizations 
• Familiarity with distributed systems (e.g., Spark, Kafka) and how they support scalable analytics solutions 
• Passion for TDD 
• A love of sports 
• Able to troubleshoot complex problems that arise during the Data Engineering process and be able to find effective solutions. 
• Communicate complex technical concepts to non-technical stakeholders and be able to work effectively with cross functional teams. 
• A side project that illustrates the individual has thought about solution architecture from start to finish

Additional Information

At Entain, we know that signing top players requires a great starting package, and plenty of support to inspire peak performance. Join us, and a competitive salary is just the beginning.

Depending on your role and location, you can expect to receive benefits like:

• Generous group bonus scheme
• Hybrid working
• Private medical insurance
• Pension Scheme - matched to 6%
• Ability to buy and sell holiday
• Free subscription to wellbeing app Unmind
• Entain & Enhance days
• Sharesave Scheme

 Join a winning team of talented people and be a part of an inclusive and supporting community where everyone is celebrated for being themselves.  

Should you need any adjustments or accommodations to the recruitment process, at either application or interview, please contact us.

Company Description

This role is for Angstrom Sports, a proprietary sports pricing and product provider, building intricate, simulation driven pricing and risk systems to support the success of key sports brands across the Entain group.

Founded in 2018 and having established itself as a pioneer in player-level, play-by-play simulations and forecasting, Angstrom was acquired by Entain in 2023. Today, we are responsible for delivering the group's most advanced pricing and risk capabilities with a focus on the US market. We're committed to building the next generation of sports betting products - sports-first, recreationally-focused, and designed to make betting more engaging, more intelligent, and more fun.

We're proud to be a high-performing, low-ego team where brilliant people are empowered and people work to become brilliant. While we're ambitious and delivery-driven, we take real pride in how we operate and the health of our independent culture, underpinned by mutual trust and respect.

Job Description

The purpose of the Data Engineer 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 key responsibilities will include:

• Designing and implementing scalable data architectures and systems
• Developing and maintaining ETL (Extract, Transform, Load) pipelines.
• Managing data storage, backup, and recovery mechanisms
• Writing SQL queries to extract data for analysis.
• Developing and implementing data security and privacy
• Interfacing with clients and end users to receive guidance on projects and deliverables.