I am a Data Engineer with a Software Engineering background, specializing in building scalable data pipelines and distributed data processing solutions using Azure Data Factory, Azure Databricks, PySpark, Delta Lake, ADLS Gen2, SQL, and Azure Fabric. My experience spans designing end-to-end ETL/ELT pipelines, implementing Medallion Architecture (Bronze, Silver, Gold), optimizing Spark workloads, building dimensional data models, and enabling analytics-ready datasets for reporting and business intelligence. Before transitioning into Data Engineering, I worked as a Software Engineer, where I built scalable backend systems using Node.js, Express.js, MongoDB, Kafka, Redis, and Microservices. I also developed production-grade applications with React Native, designed REST APIs, implemented real-time communication using Server-Sent Events (SSE) and WebSockets, and deployed cloud-native applications on GCP. This combination of software engineering and data engineering allows me to build reliable, high-performance data platforms while understanding the complete journey of data—from application events to analytics-ready insights. I enjoy sharing practical content on Data Engineering, Azure, PySpark, SQL, Spark, Data Warehousing, System Design, and interview preparation, helping engineers build strong fundamentals and crack top Data Engineer roles.