Azure Data Engineer with 5 years of experience in designing and developing scalable cloud data solutions using Microsoft Azure and Microsoft Fabric. Expertise in Azure Data Factory, Azure Databricks, Synapse Analytics, P…
Azure Data Engineer with 5 years of experience in designing and developing scalable cloud data solutions using Microsoft Azure and Microsoft Fabric. Expertise in Azure Data Factory, Azure Databricks, Synapse Analytics, PySpark, SQL, Delta Lake, and Lakehouse Architecture for building high-performance ETL/ELT pipelines. Experienced in data integration, data transformation, Medallion Architecture, data modeling, and performance optimization across enterprise data platforms. Skilled in delivering secure, reliable, and analytics-ready datasets using Azure best practices.
<p>Designed and developed a scalable Azure analytics platform to improve data processing efficiency and performance.<br>
Built end-to-end ETL pipelines using Azure Data Factory, integrating APIs, on-premises databases, and flat files into Azure Data Lake Storage.<br>
Developed and optimized Azure Databricks pipelines with Delta Tables, implementing schema enforcement and data versioning for reliable data processing.<br>
Integrated Azure Key Vault for secure credential management and optimized Spark jobs to improve performance and reduce costs.<br>
Monitored and resolved pipeline failures using Azure Monitor, Log Analytics, and Application Insights.<br>
Worked with Microsoft Fabric and implemented Lakehouse Architecture to support scalable analytics and data management.</p>
<p>Using self-hosted IR on Azure App Services<br>
Optimized existing software systems, achieving a notable improvement in performance and reliability<br>
Creating serverless solutions using Azure Functions and Logic Apps<br>
Implementing CI/CD pipelines<br>
Managing and querying Azure SQL Databases<br>
Working with Azure Blob Storage and Key Vault for secure data management</p>
<p>Built end-to-end data pipelines in Microsoft Fabric using Data Factory, Dataflows Gen2, Pipelines, and Lakehouse to ingest, transform, and process manufacturing data.<br>
Designed and implemented the Medallion Architecture (Bronze, Silver, Gold) using Delta Tables and OneLake for scalable, governed, and high-performance data management.<br>
Developed PySpark notebooks for data cleansing, transformation, aggregation, enrichment, and business rule validation on large-scale datasets.<br>
Optimized Spark jobs and ETL workflows through partitioning, caching, and efficient transformations, improving pipeline performance and reducing processing time.<br>
Implemented automated pipeline scheduling, monitoring, and failure alerting to ensure reliable and timely data processing.<br>
Collaborated in Agile Scrum ceremonies, including sprint planning, daily stand-ups, sprint reviews, and production support.</p>
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