Key Responsibilities Design, develop, and maintain scalable data pipelines using Microsoft Azure services. Build and manage ETL/ELT workflows for data extraction, transformation, and loading. Develop data integration solutions using Azure Data Factory (ADF).

Work with Azure Databricks to process and transform large datasets. Develop and optimize SQL queries, stored procedures, and data models. Implement data processing solutions using Python, PySpark, and Spark SQL.

Work with Azure Data Lake Storage (ADLS Gen2) for data storage and management. Design and maintain data warehouses and data lake solutions. Implement data quality checks, validation, and monitoring processes.

Optimize data pipelines for performance, scalability, and cost efficiency. Implement data security, access controls, and governance. Troubleshoot and resolve data pipeline and integration issues. Collaborate with data analysts, data scientists,



and business stakeholders.

Deploy and manage data solutions using Azure DevOps and CI/CD pipelines.

Preferred Skills Strong knowledge of SQL and database concepts. Hands-on experience with Microsoft Azure cloud services.

Experience with Azure Data Factory (ADF). Knowledge of Azure Databricks and Apache Spark. Robust programming knowledge in Python and PySpark.

Experience with Azure Data Lake Storage (ADLS Gen2). Knowledge of ETL/ELT processes and data pipeline development.

Experience with Azure Synapse Analytics. Knowledge of data warehousing and dimensional modeling.

Experience with Spark SQL and Delta Lake. Understanding of batch and real-time data processing. Knowledge of data integration and data transformation techniques.

📌 Azure Data Enginee (Canada)
🏢 Spait Infotech
📍 Canada