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Mid-level data engineer title with 3+ years and generalist skills increases applicant competition.
Microsoft Fabric specialization reduces cross-industry portability, though core data engineering skills remain transferable.
Explicit 3+ years plus mandatory Microsoft Fabric, PySpark, SQL and Azure stack makes screening strict.
Design, develop, and maintain scalable data solutions using Microsoft Fabric components including Lakehouse, OneLake, Data Warehouse, and Data Factory.
Build and optimize ETL/ELT pipelines, data transformation workflows with Python, PySpark, SQL, and Fabric Notebooks integrating multiple enterprise data sources.
Implement and support deployment including CI/CD for Microsoft Fabric workloads, ensuring data quality, validation, and performance optimization.
3+ years of Data Engineering experience with Azure Data Platform and Microsoft Fabric.
Hands-on expertise with Fabric Data Factory, Pipelines, Dataflows Gen2, OneLake, Fabric Lakehouse, Data Warehouse, and Notebooks.
Proficient in SQL/T-SQL, Python, PySpark, ETL/ELT development, data modelling, and integration of REST APIs.
Familiarity with Azure ecosystem components like Azure Data Factory, Azure SQL, ADLS, Azure Synapse and experience with Delta Lake and Medallion Architecture.
Has practical experience building and deploying Microsoft Fabric solutions end-to-end, beyond certifications or theory.
Comfortable explaining architecture, pipelines, transformations, and Fabric components they personally implemented.
Experienced in integrating multiple data sources, optimizing data models for analytics, and supporting enterprise-scale data platforms.