Job description

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.

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