You will be prepared to get stuck into any problem, across any part of the technology landscape. You will have a can‑do attitude and will enjoy being outside of your comfort zone as you try to solve problems, large and small.
You will be responsible for helping to improve our platform by working with the team to create tooling and processes that the development and test teams can use to drive performance, productivity, and best practices. You will also work within the team to make improvements to existing features across the full stack of our platform, ensuring they are delivered on time with the correct approach and to the standards defined by the development leads.
Responsibilities
* Design, develop, and maintain data pipelines and ETL processes using AWS services such as AWS Glue, AWS Lambda and AWS S3.
* Support the migration of the existing Data Warehouse from SQL Server to AWS through S3 and Redshift.
* Develop and implement data quality checks and validation procedures.
* Design and implement best practice data lakehouse architectures and data warehousing solutions.
* Collaborate with data scientists and analysts to support the deployment of machine learning and advanced analytical solutions.
* Develop and maintain data documentation and operational procedures.
* Investigate and resolve data quality issues and performance bottlenecks.
* Stay abreast of the latest data technologies and industry best practices.
* Mentor junior data engineers and provide technical guidance to other team members where applicable.
* Contribute to the development and improvement of data platform best practices.
* This list is not exhaustive, and you may be required to undertake additional duties, not listed, that are considered reasonable and are aligned to your role.
Experience and Skills
* Experience: Significant commercial experience (5+ years) as a Data Engineer in a high-transactional, high-volume data environment, ideally within the betting, gaming, or fintech industries.
* Programming: Strong proficiency in Python or Scala for data manipulation, automation, and pipeline development.
* Cloud expertise: Extensive hands‑on experience with a major cloud provider, particularly AWS, including services like AWS Glue, AWS Lambda, and Amazon S3.
* Data processing: Expertise in big data processing frameworks such as Apache Spark and experience with real‑time streaming technologies like Apache Kafka.
* SQL: Expert‑level SQL skills for complex data querying, manipulation, and optimization within a data warehouse environment.
* ETL/ELT: In‑depth knowledge of ETL/ELT methodologies and tools, with experience in designing and building efficient data pipelines.
* Communication and problem‑solving: Excellent communication and collaboration skills, with the ability to solve complex technical data problems with a clear, logical approach.
* Betting industry background: Experience with real‑time sports betting data, game stats, or fantasy sports is highly desirable.
* DevOps and CI/CD: Familiarity with DevOps principles and experience with CI/CD tools (e.g., Terraform, Jenkins) for deploying and managing data infrastructure.
* Data modelling: Experience with dimensional modelling and designing robust data schemas for analytical use cases.
* Data Lakehouse architecture: Experience designing and implementing modern data Lakehouse architectures is a plus.
* Observability: Familiarity with monitoring and alerting tools (e.g., Grafana, Datadog) for data pipelines.
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