About the Role
We are seeking a highly skilled Data Engineer – Microsoft Fabric (PySpark) to design, develop, and optimize modern data engineering solutions on the Microsoft Fabric platform. The ideal candidate will have solid expertise in PySpark, Spark SQL, Microsoft Fabric Lakehouse, Data Factory Pipelines, and ETL/ELT development, with the ability to build scalable, high-performance data processing solutions for enterprise analytics.

Key Responsibilities
Design, develop, and maintain scalable data processing solutions using PySpark within Microsoft Fabric.
Build, optimize, and manage ETL/ELT pipelines for processing large-scale structured and semi-structured datasets.
Develop high-performance data transformation workflows using Spark DataFrames and Spark SQL.
Create and maintain robust data ingestion, transformation, and aggregation pipelines using Fabric Notebooks, Lakehouse, and Data Factory Pipelines.
Implement best practices for data engineering, including performance tuning, partitioning, caching, and query optimization.




Design reliable and reusable data models to support business intelligence and advanced analytics initiatives.
Collaborate with data architects, analysts, and business stakeholders to understand data requirements and deliver scalable solutions.
Monitor pipeline execution, troubleshoot failures, and optimize workloads for reliability and efficiency.
Ensure data quality, governance, and security standards are followed across all data engineering processes.
Document technical solutions, workflows, and deployment processes to support operational excellence.

Required Skills & Qualifications
Strong hands-on experience with Microsoft Fabric and PySpark.
Expertise in Spark SQL, Spark DataFrames, and distributed data processing.
Experience building enterprise-grade ETL/ELT pipelines.
Hands-on experience with Fabric Notebooks, Lakehouse, and Data Factory Pipelines.
Strong understanding of data ingestion, transformation, aggregation, and orchestrati

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