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Mid-level Bangalore data role with PySpark specialization and common title, moderate candidate competition.
PySpark and ETL skills transfer across industries but Microsoft Fabric platform specificity increases sensitivity.
Explicit 5-7 years plus mandatory PySpark, Microsoft Fabric, and ETL pipeline experience.
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Design and develop scalable data processing solutions using PySpark within Microsoft Fabric environment.
Build and optimize ETL/ELT pipelines for large-scale structured and semi-structured datasets using Spark DataFrames and Spark SQL.
Create data ingestion, transformation, and aggregation workflows leveraging Fabric Notebooks, Lakehouse, and Data Factory Pipelines.
5-7 years of relevant work experience in PySpark development.
Hands-on experience with PySpark on Microsoft Fabric platform.
Strong skills in building and optimizing ETL/ELT pipelines for large datasets using Spark technologies.
Work Experience Required: 5-7 years
Proven ability to handle end-to-end data pipeline development and optimization in a big data environment.
Experience working with Microsoft Fabric ecosystem components like Notebooks, Lakehouse, and Data Factory Pipelines.
Candidate likely excels in deep technical expertise in PySpark and scalable data processing frameworks aligned with enterprise-grade solutions.