Data Engineer

Overview

Level: Mid-level to senior,based on the required 5+ years of hands‑on Azure Databricks and Spark experience.

Summary: This role is focused on building and supporting large‑scale data pipelines using Azure Databricks, Spark, Python/PySpark, and SQL. The candidate should have strong hands‑on engineering experience with production data processing, data lake architecture, ETL, data quality, and Azure analytics services. This is a technical delivery role that also requires strong documentation and communication skills.

Main Responsibilities:

• Build and implement data pipelines using Azure Databricks and Spark.
• Write optimized Python/PySpark and SQL code for very large, TB-scale data processing.
• Design and maintain data lake architecture and ETL workflows.
• Manage data quality, integrity, and validation.
• Use Azure data services for storage, processing, and analytics.
• ...