Senior Engineer/Senior Azure Data Engineer � Azure Synapse, Databricks & Power BI
Rockville, MD, US
28 days ago
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Summary
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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