Address- Analytics Engineering builds and maintains DAZN s Data Model and supports the on-going technical delivery of the Data Engineering team's outputs.
- We are responsible for the sourcing and modelling of DAZNs core data models, driving our corporate and product analytics, predictive modelling and data exchanges with rights holders and other parties.
- We also play a key role in mentoring data scientists, analysts and engineers in delivering reliable, timely, and consumable insights for business wide applications.
- Most of our datasets are stored in Snowflake, modelled with dbt and orchestrated using Airflow in a 100% cloud-based platform, largely using AWS.
- We work closely with Data and Data Platform engineers who provide the infrastructure we need to deliver data products.
- Maybe just have this as We work closely with Data Engineers who provide the infrastructure required to deliver datasets to end users.
- Develop and maintain ELT data pipelines.
- Ensure our Source of Truth datasets are stable, accurate, reliable and efficient.
- Work with data users to understand their needs and create data products to support them.
- Grow and improve the quality of our analytics code base.
- Design and implement testing frameworks to monitor data quality.
- Drive continuous performance improvements and efficiency savings within our data stack and wider analytical tooling.
- Deliver projects in an agile, scrum-based environment with a highly collaborate, hybrid team.
- Experience coding with SQL for analytics as well as data modelling
- Experience using cloud-based Data Warehouses (Snowflake, Redshift etc)
- A good understanding of Data Warehousing concepts and cloud ETL/ELT design patterns (star schemas, de-normalisation, batch vs real-time etc)
- Comfortable in designing efficient and robust ELT workflows
- Working knowledge of CI/CD processes
- A Team Player approachable, collaborative and flexible, and comfortable working in hybrid teams
- Experience working with dbt and Airflow
- Programming experience in Python
- Experience working in an agile, scrum-based environment
- Experience as a data consumer in analytics, data science or BI
Skills: Sql, Etl, ELT, Airflow, Data Warehousing, Python, dbt
Experience: 0.00-2.00 Years
