Fast and efficient unstructured data extraction. Written in Rust with bindings for many languages.

Data pipelines from re-usable components

The open-source Useful SDK. One python decorator in the Useful library allows for full observability of Python functions within an ETL.

A project structure for doing and sharing data engineer work.

Lien de l'application

e-Portfolio showcasing my personal projects.

Build ETL piplines on AirFlow to load data from BigQuery and store it in MySQL

Sparkify project

AutoDS-Prep automates the data pre-processing step of Data Science Projects.

This repo contains the DAGs that run on my local Airflow environment. I use the local environment to test my DAGs before deploying them to virtual machines via Kubernetes

JSON-driven ETL pipeline framework prototype

An extension that registers all pharmacies in Argentina.

A deployed machine learning model that has the capability to automatically classify the incoming disaster messages into related 36 categories. Project developed as a part of Udacity's Data Science Nanodegree program.

Weaving together different threads (services like image/audio converse, ETL services, etc.) to enable the World Wide Flow

A Python and Spark based ETL framework. While it operates within speed limits that is framework and standards, but offers boundless possibilities.

This project demonstrates a complete ETL pipeline for Formula 1 racing data using Azure Databricks, Delta Lake, and Azure Data Factory. It covers data ingestion, transformation with PySpark and Spark SQL, data governance with Unity Catalog, and visualization through Power BI. Designed to showcase real-world data engineering workflows in Azure.