This project builds an End-to-End Azure Data Engineering Pipeline, performing ETL and Analytics Reporting on the AdventureWorks2017LT Database.

End-to-end Azure Data Engineering pipeline using ADF, Databricks (PySpark), ADLS Gen2, Azure SQL, and Power BI for COVID-19 analytics

GitOps-driven Azure Data Factory pipeline that ingests multi-source data (GitHub + ADLS) into ADLS Bronze using dynamic, parameterized ETL workflows.

End-to-end real-time data pipeline using Kafka, Spark, Delta Lake, DuckDB, and Power BI. Simulates clickstream analytics with batch + streaming workflows for modern data engineering.

This project builds an End-to-End Azure Data Engineering Pipeline, performing ETL and Analytics Reporting on the AdventureWorks2017LT Database.

Designed and implemented an end-to-end Azure Data Engineering platform using Azure Data Factory, ADLS Gen2, Databricks, Synapse Analytics, and Power BI. Built metadata-driven pipelines and Medallion Architecture (Bronze, Silver, Gold) to ingest, transform, and serve analytics-ready data.

End-to-End Azure Data Engineering Project: Tokyo Olympics 2021 Analysis A complete data pipeline built on Microsoft Azure to ingest, process, and analyze Olympic data.

Power BI dashboard analyzing client credit default patterns

Designed a production-grade Azure Data Engineering project centered on Azure Data Factory. Built dynamic, metadata-driven pipelines to ingest data from on-prem systems, REST APIs, and Azure SQL into ADLS Gen2 using Medallion Architecture, incremental loading, and enterprise-scale orchestration patterns.

End-to-end Azure Databricks retail data engineering project using Medallion Architecture (Bronze, Silver, Gold). Implements Auto Loader, Unity Catalog, Delta Lake, SCD Type 1 & 2 dimensions, and Fact Orders for analytics-ready star schema modeling.

📊 Analyze sales data and forecast future revenue using Python. Gain insights into performance metrics and optimize your business strategies effectively.