Data Platform Engineer

What's your new role about?
The Data Platform team is responsible for building infrastructure, services and tooling to support data engineering and data discovery. We look to deliver a robust and reliable platform that meets our users' requirements, while also testing out new and emerging technologies to add to our stack. Key to the team's mentality is continuously making improvements, automation of processes, using metadata to drive optimization and help other data teams to get stuff done.

You will have the opportunity to play a part in a wide array of projects rooted in DAZN's unique and exciting data, whilst demonstrating ground-breaking tools and techniques that support our ambitious plans for product development and the company's rapid global growth to change the way the world watches sport!

Some of the latest Data Engineering projects include:

· Move existing services & pipelines to Kubernetes

· Improve existing services and add new ones to the Data Platform

· Delivering a data discovery and metadata engine

· Building out an “exchange layer” to securely move data to other data platforms

If you are interested in building a modern data platform and are interested in joining the DAZN journey, then we would love to hear from you.

As a Data Platform Engineer, you'll have the opportunity to:

• Help shape the future of the Data Platform that we are building
• Lead the design and implementation of new platform feature & data products that will improve the experience of people working with data at DAZN
• Work on tooling for our Data Engineering teams, to automate tasks and make it easier for them to deliver value from our data
• Contribute to the ongoing improvement of our engineering processes, standards and documentation
• Mentor junior engineers and help them develop their skills

You will be set up for success if you have:

• Several years of experience as a Platform or Data Engineer, writing clean, robust and testable code, preferably in Python, whether functional or object-oriented
• Strong understanding of cloud-vendor technologies, such as AWS, GCP or Azure
• Experience with infrastructure-as-code and CI/CD processes
• Working knowledge of SQL and knowledge of Data Warehousing concepts
• Working experience with open-source orchestration tools like Airflow
• Exposure to Docker, Kubernetes and/or streaming technologies such as Kinesis, Apache Flink, Apache Kafka

Even better if you have:

• Experience using AWS services, such as S3, Lambda, IAM, EMR, EKS, Firehose and EventBridge
• Experience working on Terraform for cloud infrastructure management.
• Experience working on MPP Databases like Snowflake, Redshift
• Experience working with Apache Spark
• Worked with Data Lake Table Formats such as Apache Iceberg or Delta Lake
• Hands-on knowledge of building data pipelines, either batch, event-driven or streaming
• Familiarity with dbt, data modelling and data quality testing
• Experience in implementation/productionize open-source tools.