Description

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT data pipelines using Azure Data Factory and Snowflake
• Develop data ingestion and transformation workflows from multiple structured and unstructured data sources
• Build and maintain data warehouse solutions using Snowflake with dimensional data models
• Develop complex SQL queries, stored procedures, views, tables, and data transformations
• Implement data ingestion pipelines using Snowpipe and other Snowflake loading mechanisms
• Work with Azure Data Lake Storage (ADLS Gen2) for data storage and integration
• Develop data transformation processes using Python and/or PySpark on Azure Databricks
• Optimize Snowflake queries, warehouse performance, storage, and compute costs
• Implement CI/CD processes for data engineering workflows using Azure DevOps/Git
• Follow data security, governance, access control, and compliance best practices

Qualifications

• 5+ years of experience in Data Engineering with strong hands-on Microsoft Azure experience
• Strong experience with Snowflake including SnowSQL, Snowpipe, and performance optimization
• Hands-on experience with Azure Data Factory (ADF) and Azure Data Lake Storage Gen2
• Strong SQL development and query optimization skills with data warehousing expertise
• Experience with Python and/or PySpark for data transformation processes
• Experience with Azure Databricks for large-scale data processing and transformation
• Experience with Git and Azure DevOps for CI/CD implementation
• Strong troubleshooting, analytical skills, and ability to document technical designs

Key Skills

Education

Bachelor's degree