Lead Data Engineer

We are looking for a Lead Data Engineer to join the Data and Platforms team within Flutter Functions Global Platforms department. Youll be working within a squad dedicated to our Global Sportsbook and Trading business vertical. GSTs mission is to empower our brands to shape the future of sports betting. You'll be provided to work on a greenfield data platform based on AWS and Databricks with datasets that range from the global Bet Stream processes 4B bets yearly through to our odd pricing services which can generate hundreds of thousands updates for a single sporting event. We are building a unique operating model where we are lead by our Data as a Product mindset.

This role follows a hybrid approach to working, allowing you to combine working from home with working in our modern offices. These discussions are between you and your manager to find the best pattern for you both! We will kit you out to work from home but know that working as a team is what makes us great and spending quality time together is essential for keeping us mission aligned.

If you are a passionate Data Engineering Professional, you have the chance to be part of a team that looks to build out our next-generation data platform, leveraging new technologies and techniques to maximize the business value out of our data assets and empower innovation.

KEY RESPONSIBILITES

• Lead data and process innovation for our organization through robust delivery of exceptional solutions. Act as the technical lead for your squad.
• Work closely with Product and Delivery teams to determine the best strategy to deliver the roadmap.
• Balance the commercial needs of the business against the ideal technical design, providing input on estimations, conducting spikes, and supporting the creation of strategic and pragmatic delivery plans.
• Regularly communicate the status of delivery to the team and the Engineering Manager, highlighting any risks and potential impacts, and proactively develop mitigation strategies.
• Mentor and coach more junior members of the Data Engineering Department.
• Transform raw data into useful data products.
• Strive for efficiency by aligning data products with business goals.
• Support our implemented BI solutions by monitoring and tuning performance queries and data processes, addressing user questions concerning data integrity, and communicating functional and technical issues.
• Contribute to choosing the right technology and ensuring proper data design and implementation in various projects and solutions.
• Demonstrate hands-on skills in processing large data sets, expertise in data structure, data access patterns, Big Data concepts, and cloud computing.
• Optimize data systems and pipelines for performance, scalability, and cost-effectiveness.
• Deliver excellent production quality code, mentor other developers to do so, and promote the production of reusable code and modules where appropriate, applying principles of Agile delivery.
• Work closely with other team members and subject experts to ensure accurate and effective support documentation is maintained.
• As driven by availability requires join on-call rota for data products supported by data engineering or for specific events that matter (large sporting events).

TO EXCEL IN THIS ROLE, YOU WILL NEED TO HAVE

• 6+ years of experience in development, deployment and operation of data technologies and platforms
• Experience in designing scalable cloud data processing and warehousing solutions.
• Experience in designing and implementing efficient ETL processes and data pipelines.
• Experience with Agile software development and DevOps practices
• Experience and knowledge in data migration techniques and processes
• Proven ability to collaborate with technical and business teams and communicate effectively across channels.
• Excellent knowledge and experience of one of the cloud big data solutions such as the AWS Glue Ecosystem, Microsoft Fabric and GCP. Demonstratable experience of using Databricks in one of these settings is a bonus.
• Excellent knowledge and experience in SQL, database performance optimization and working with large datasets.
• Understanding of database and analytics technologies in the industry including Relational, Vector, Graph and NoSQL databases.
• Data integration experience from streaming sources such as Kafka and/or Apache Pulsar.
• Deep understanding of data warehousing and data architecture concepts. Experience with Data Vault modelling is a plus
• Experience with Python scripting, Spark and SQL for data engineering
• Experience with CI/CD solutions (i.e Github, argoCD, artifactory etc.)