Senior Azure Data Engineer

Role Overview

• Design and build robust, reusable, parameter-driven ingestion and transformation pipeline using Azure Data Factory
• Implement medallion architecture on Azure Data Lake Storage Gen2
• Build performant ELT workflows that leverage pushdown to source systems
• Develop and optimize PySpark notebooks and jobs on Azure Databricks or Synapse Spark
• Design dimensional models and data vault patterns for analytics consumption
• Implement Slowly Changing Dimensions and Change Data Capture
• Tune distributed SQL workloads in Synapse Dedicated SQL Pool
• Implement CI/CD for data pipelines using Azure DevOps
• Instrument pipelines with robust logging and monitoring
• Lead or contribute to legacy-to-cloud migrations

Requirements

• 5+ years of data warehouse development experience
• 5+ years of data modeling experience using ERWIN or similar tools
• 2+ years of experience with Azure Data Factory and Snowflake
• Deep hands-on expertise with Azure Data Factory
• Strong Experience in Data Bricks and PySpark
• Strong working knowledge of Azure Data Lake Storage Gen2
• Experience with Azure Key Vault, Azure AD / Entra ID
• Monitoring and troubleshooting with Azure Monitor
• Advanced SQL — window functions, CTEs, query optimization
• Strong Python for data engineering — pandas, PySpark

Tech Stack

• Azure
• Cloud
• Pandas
• PySpark
• Python
• Spark
• SQL
• Vault

Benefits

• Flexible work arrangements