Description
Builds and runs large scale batch data pipelines, keeping jobs fast and affordable as data volumes grow. Works with Apache Spark to build and manage large scale data processing jobs, including performance tuning to maintain efficient and reliable pipeline execution. Supports data modelling for analytics and organises data in a lakehouse so it is usable downstream. Handles automated scheduling, monitoring, and data quality checks, while working with platform and product teams on end to end data flows.
Requirements
Requirements
- Strong hands on Apache Spark including performance tuning, not Spark usage through a managed notebook only.
- Data modelling for analytics and organising data in a lakehouse so it is usable downstream.
- Automated scheduling, monitoring, and data quality checks.
- Works with platform and product teams on end to end data flows.
- Apache Iceberg or other open table formats.
- Trino or similar query engines.
- On premises or self managed cluster experience.