Hello, I'm Darshan – an experienced and passionate Data Engineer with deep expertise in Azure technologies (ADF, ADB, ADLS Gen2), Microsoft Fabric, and Apache Spark (PySpark, Scala, Spark SQL) for building scalable, cloud-based data architectures. With a proven background in designing and implementing distributed data pipelines, I specialize in end-to-end batch and streaming data processing systems that transform complex data into actionable insights. I bring robust experience in developing and operationalizing Big Data solutions using the Azure and Microsoft Fabric ecosystems, enabling efficient, secure, and high-performing data workflows in enterprise environments. In my current role, I work extensively with Microsoft Fabric, Azure Data Factory, Azure Data Lake Storage Gen2, Azure Databricks, and other Azure-native services. I architect and build modern, metadata-driven data platforms—migrating legacy systems, optimizing data flows, and ensuring seamless data availability for analytics, BI, and AI workloads. My experience in Microsoft Fabric includes working with Lakehouses, Fabric Data Pipelines, Notebooks, Warehouses, and OneLake to deliver unified, scalable data solutions aligned with business and governance requirements. I collaborate closely with data architects, business analysts, and engineering teams to implement scalable, cloud-first data solutions that meet performance, security, and cost-efficiency goals. Technical Proficiencies ★ Microsoft Fabric: Lakehouse, Pipelines, Warehouse, Notebooks, OneLake ★ Azure Cloud: Azure Data Factory (ADF), Azure Data Lake Storage (ADLS Gen2), Azure Databricks, Azure DevOps ★ Big Data Ecosystem: Apache Spark, HDFS, Hive, HBase ★ Languages: Scala, Python, SQL ★ Databases: Teradata, SQL Server, MySQL ★ API Framework: Python Flask ★ Scheduling/Orchestration: Airflow,, Ctrl-M, ADF ★ Platforms: Microsoft Fabric, Azure, Cloudera