Senior Engineer/Senior Azure Data Engineer Azure Synapse, Databricks & Power BI

Job Summary: We are looking for a highly skilled Azure Data Engineer to design and implement modern data solutions using the Azure cloud ecosystem. The ideal candidate will have deep expertise in Azure Data Lake (Gen1/Gen2), Data Factory, Databricks, Synapse Analytics, and Power BI, with a strong understanding of data streaming, data warehousing, and security components in Azure. This role requires a hands-on professional who can build scalable, secure, and high-performing data platforms that drive analytics and business insights.
Job Locations: Feasterville-Trevose, Pennsylvania OR Rockville, Maryland Key Responsibilities:

• Design and develop robust data pipelines using Azure Data Factory and Azure Databricks.
• Work with streaming data processing using Spark clusters in Azure Databricks.
• Manage and utilize Azure Data Lake Gen1/Gen2, Blob containers, and Azure SQL Server for data storage and processing.
• Build and maintain Azure Data Warehouses and deliver scalable solutions using Azure Synapse Analytics.
• Implement secure data access and management using Azure Key Vault and Azure Active Directory.
• Integrate event-driven architecture using ESB, Event Grid, and Azure Functions.
• Work with Cosmos DB for NoSQL database solutions within cloud-native applications.
• Develop and publish interactive dashboards and analytics reports using Power BI.
• Ensure security, compliance, and performance of data infrastructure.

Must-Have Skills:

• Strong experience with:
  • Azure Data Lake Gen1/Gen2
  • Azure Data Factory
  • Azure Databricks (including Spark clusters)
  • Azure Synapse Analytics
  • Azure SQL Server, Cosmos DB, Blob Storage
  • Azure Key Vault, Azure Active Directory
  • Azure Functions, Event Grid, ESB
• Mandatory experience with Power BI for analytics and dashboard creation.

Preferred Skills:

• Experience in building end-to-end data pipelines for big data and analytics.
• Knowledge of data governance and data security best practices in Azure.
• Familiarity with DevOps for Data Engineering and automation of deployments.