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Mid-level data engineer title, metro locations, and generalist skillset increase applicant competition.
Azure-specific data platform experience required, but core data engineering skills remain moderately transferable across industries.
Explicit 3–8 year requirement plus mandatory Azure Fabric/Databricks/PowerBI skills makes filters strict.
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Own the full software development lifecycle for Azure Data Platform applications in a DevOps environment.
Design, develop, test, and support scalable data engineering solutions on Microsoft Azure Data Platform.
Lead best practices in craftsmanship, security, resilience, and performance optimization of data solutions, including mentoring peers.
3-8 years experience in MSBI with at least 3 years hands-on work on Azure Data Platform.
Bachelor's degree in Engineering/Math/Statistics/Econometrics or related discipline.
Strong experience with Azure data services including T-SQL, SSIS, SSAS, SSRS, Azure Data Factory, Azure Data Lake Store, Azure SQL DB, Azure SQL DW, Azure Analysis Services, and Power BI.
Intermediate-level hands-on skills with Microsoft Fabric components: Pipelines, Dataflows Gen2, ADLS Gen2, Notebooks, Lakehouse, Warehouse, Delta tables.
Experienced in building scalable, optimized end-to-end data pipelines and implementing incremental load strategies using Azure data analytics platform.
Strong SQL skills with expertise in complex transformations, query optimization, and performance tuning for distributed data processing.
Comfortable working collaboratively in Agile teams and driving technical mentorship across Azure data platform solutions.