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Popular mid-level data engineer role (4-6 yrs) but Microsoft Fabric niche reduces applicant pool.
Core data engineering skills transferable, but Microsoft Fabric and Azure specifics increase domain bias.
Explicit 4-6 years plus mandatory Microsoft Fabric, Azure and PySpark skills enforce strict filters.
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Design, develop, and maintain scalable data ingestion and transformation pipelines using Microsoft Fabric and related technologies.
Develop and optimize Fabric Lakehouse environments implementing Medallion Architecture for data quality and governance.
Collaborate with BI teams to support Power BI semantic models and ensure data quality, consistency, and accuracy across platforms.
4-6 years of experience in data engineering or related field.
Bachelor's degree in Computer Science, Data Science, or a related field.
Proficiency with Microsoft Fabric components including OneLake, Fabric Lakehouse, Data Factory, Data Pipelines, and Notebook development.
Strong skills in PySpark, Spark SQL, SQL, Delta Lake, and experience with Azure Data Services (ADLS, Azure Synapse preferred).
Experienced in large-scale enterprise data transformation programs with deep knowledge of Microsoft Fabric and Azure data platform.
Proven ability to implement Medallion Architecture and advanced data engineering best practices including ETL/ELT, data modeling, and governance.
Familiarity with integrating data from diverse sources and collaborating closely with BI teams for analytics and AI/ML use cases.