Azure Data Engineer (Data Lake Ownership)
Summary
Build and own an Azure-based data lake and Spark pipelines, then run BAU: monitoring, performance, cost, and governance for a business-critical analytics platform.
This role requires a hands‑on Data Engineer who has personally delivered and operated a full data lake on Azure. You will initially partner on build, then take full ownership of platform performance, scalability, and evolution.
Client Details
A multi‑regional organisation undergoing a large‑scale digital transformation focused on modern data platforms. The business is investing heavily in enterprise‑grade cloud, data, and analytics capabilities.
Description
- Design and build Azure‑based data lake (ADLS, ADF, Synapse/Fabric)
- Develop production‑grade Spark pipelines (batch & near real‑time)
- Own data modelling for Power BI (star schema, semantic layers)
- Implement data governance, lineage, and quality controls (e.g. Purview)
- Take full ownership of platform BAU: monitoring, performance, cost
Profile
- 5‑7 years’ Data Engineering experience with at least 1 full data lake delivery
- Expert in Azure stack (ADF, ADLS, Synapse/Fabric) + strong PySpark
- Proven ownership of production pipelines (design, deploy, operate)
- Strong SQL & Python; experience with APIs, ERP integrations (e.g. D365)
- Demonstrated experience structuring data specifically for Power BI
Job Offer
- End‑to‑end ownership of a business‑critical data platform
- Exposure to large‑scale transformation and senior stakeholders
Skills
Azure Data Engineer