Data Engineer: Spark, SQL & Airflow on AWS
Summary
Build and maintain scalable data pipelines using Spark, SQL, Python, and Airflow on AWS to ensure clean, reliable data flows for analytics and governance.
DysrupIT is seeking a data engineer to collaborate with data architects and independently analyze and model data. You will implement scalable data pipelines, ensure data quality, and support end-to-end data flows across multiple systems.
The role requires strong SQL, data preparation and integration skills, and experience with Spark, Python, Airflow and cloud services. You will work in an Agile setting to drive insights and governance across data assets.