🚀 Build Azure applications quickly with this production-ready template, offering multiple tech stack options for easy project initialization and development.

🌐 Build scalable data pipelines that work across Azure and Google Cloud Platform with minimal changes using this production-ready framework.

🏥 Streamline healthcare claims processing with this Snowflake pipeline, featuring auto-ingestion, CDC, SCD Type 2, and data quality checks.

🌥️ Build a complete Azure data pipeline for seamless migration, ETL, and analytics from on-premise databases to the cloud, leveraging Power BI for insights.

🔄 Build scalable ETL pipelines on Azure using PySpark, transforming raw data into analytics-ready datasets with a focus on Medallion Architecture.

🌍 Ingest and transform real-time earthquake data using Azure tools to deliver reliable analytics-ready datasets for insightful decision-making.

An end-to-end Azure data engineering pipeline implementing a metadata-driven Medallion Architecture to transform raw GitHub CSV data into a structured Star Schema. The project leverages ADF, Databricks (PySpark), and Synapse Analytics to build a scalable, secure, and production-ready data warehouse.

Building a pipeline that can handle incremental load of data from on-premises and cloud service to Azure Data Lake

A cloud-based end-to-end data engineering project built on Microsoft Azure, implementing a Medallion Architecture for Healthcare Revenue Cycle Management (RCM) data.

Azure-first medallion lakehouse for NYC 311 service request analytics with implemented bronze, silver, and gold processing, reusable data quality checks, dimensional modeling, and reporting marts.

Enterprise metadata-driven ETL framework using Azure Data Factory and Databricks. Reduces deployment time by 50%.

End-to-End Data Engineering pipeline implementing a Medallion Architecture (Bronze, Silver, Gold) using Python, Docker, dbt, Azure Data Factory, and Databricks.

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End-to-End Data Engineering Pipeline using Azure Data Factory, Databricks, and ADLS Gen2 implementing Medallion Architecture (Bronze, Silver, Gold).

This project implements an end‑to‑end medallion architecture on Azure using metadata‑driven pipelines for incremental ingestion, streaming transformations in Databricks, and a Type 2 SCD gold layer built with Delta.

RideStream is a scalable Azure-based lakehouse project designed for ride-hailing analytics. It combines batch ingestion from HTTP/internal sources with streaming booking events from Event Hubs, processes them in Databricks, and delivers a clean analytics model through a silver-layer OBT and a gold-layer star schema.

A tool where a user types a request and it generates the JSON configuration for Azure Data Factory (ADF).

Description: Automated Identity Governance and Administration (IGA) framework using Microsoft Fabric and Azure ADLS Gen2 to detect "Ghost Users" across Salesforce and Jira.

Enterprise-grade, AI-ready data lakehouse on Azure using the medallion architecture — Bronze, Silver, and Gold layers built on Azure Synapse Analytics, Databricks, and Delta Lake. Includes IaC, ETL pipelines, data quality frameworks, and MLOps integration.