Bharat Kumar

Azure Data Engineer with 2.7 years of hands-on experience in designing and optimizing scalable ETL/ELT pipelines

Talent

BengaluruMember since July 27, 2026

ETLELTData MigrationData ValidationData QualityAzure Data FactoryAzure DatabricksAzure Data Lake Storage Gen2OneLakeLakehouseData WarehouseData FactoryDirect LakeSemantic ModelsSpark SQLPartitioningCachingStored ProceduresStar SchemaMedallion ArchitectureDeltaPower BIPythonPySparkGitAzure DevOpsSQL ServerDelta LakeOn Prem Data GatewaySQL Server Integration Services

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ETLELTData MigrationData ValidationData Quality

About

Azure Data Engineer with 2.7years of hands-on experience in designing and optimizing scalable ETL/ELT pipelines using Azure Data Factory, Azure Databricks, SQL Server Integration Services (SSIS), PySpark, and Microsoft Fabric. Skilled in data migration, transformation, data modeling, performance optimization, and cloud-based data engineering solutions. Experienced in migrating on-premises SQL Server workloads to Microsoft Fabric and Azure. Microsoft DP-203 certified.

Experience

Data Engineer at Nano Tech E Services (2024-01 – Present)

Developed and maintained 10+ ETL/ELT pipelines using Azure Data Factory and Azure Databricks to process 500K+ records daily, ensuring reliable and efficient data ingestion.
Developed and optimized 15+ SQL Stored Procedures for ETL processing, data transformation, and reporting requirements, improving query performance by approximately 20%.
Created parameterized Stored Procedures to support incremental data loading and automate business logic implementation, reducing manual intervention.
Designed and implemented Bronze, Silver, and Gold data layers following Medallion Architecture to support scalable batch analytics and reporting.
Automated 10+ Azure Data Factory pipelines using triggers, scheduling, and parameterization, improving workflow efficiency and reducing manual execution.
Optimized PySpark jobs using partitioning, caching, and Spark optimization techniques, reducing ETL processing time by approximately 25%.
Collaborated with cross-functional stakeholders to troubleshoot production pipeline issues, ensuring high data quality and reliable data processing.
Implemented end-to-end migration of 20+ SQL Server tables from on-premises environments to Microsoft Fabric using Azure Data Factory, achieving over 99% data validation accuracy.
Built and maintained Microsoft Fabric Lakehouse solutions using Medallion Architecture to support scalable analytics, reporting, and Power BI Direct Lake semantic models.