FabricEngineer is a comprehensive Python package designed specifically for Microsoft Fabric developers to streamline data transformation workflows and automate complex ETL processes. This package provides enterprise-grade solutions for building robust data pipelines with minimal boilerplate code.

A full-stack financial application featuring real-time forex rates and machine learning-powered price predictions across multiple currency pairs. Built with automated data pipelines and Prophet time series forecasting.

An end-to-end, multi-container solution for collecting and visualizing stock market data

End-to-end data pipeline transforming Olist e-commerce data through Azure cloud services. Implements medallion architecture (Bronze-Silver-Gold) with multi-source ingestion, Spark-based processing, and OLTP-to-OLAP optimization for analytics-ready datasets.

End-to-End PV Monitoring & Streaming Pipeline with Delta Lake

This project is an end-to-end machine learning pipeline for predicting diamond prices based on various features. It includes data preprocessing, model training, and prediction scripts, and is designed for easy setup and use by anyone familiar with Python and data science.

Data automation involves automating the extraction, transformation, and loading (ETL) processes to streamline data workflows. GitHub Actions enables automated execution of tasks, such as building, testing, and deploying code, in response to events. This integration simplifies continuous deployment and ensures repeatable data pipeline operations

Automated pipeline to scrape and compare gaming gear prices & ratings from Amazon and eBay, including laptops, mice, Nintendo Switch, PS5, and Xbox. Outputs daily CSVs, SQL-ready datasets, and marketplace insights for competitive analysis.