You build and look after the data pipelines that power our reporting, analytics and AI work, so teams can rely on the numbers they see.
Key Responsibilities
- Design, build and maintain dependable batch and streaming data pipelines
- Model data and load it into warehouses and lakes on AWS or Azure
- Watch pipeline health, data quality and running cost, and fix problems quickly
- Partner with analysts and developers to turn raw data into trusted datasets
- Keep clear documentation of data flows, schemas and owners
Required Skills
- Good SQL and Python skills
- Understanding of ETL/ELT, data modelling and warehousing concepts
- Some experience with a cloud platform (AWS or Azure) and Git
- A careful attitude to data quality, testing and documentation
Nice to Have
- Experience with Airflow, dbt or Spark
- Exposure to PostgreSQL, MongoDB or Redis
Tools and technologies: Python; SQL; Airflow / dbt; AWS or Azure; Git
How to prepare
- Be ready to talk through a pipeline you built and how you checked its output
- Revise joins, window functions and data modelling basics