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

The simplest way to run Python on lot's of computers.

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.

Clean API primitives for data cleaning in Pyspark. Inspired by PyJanitor, Dataprep.AI and Shadcn.

Lien de l'application

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

DataSift auto applies a data pre-processing pipeline to Data Science Projects.

Big Data ETL pipeline for Brazilian e-commerce data. Implements data ingestion, transformation, and storage using Apache Spark, Hadoop, and SQL. Designed for scalable data processing and analytics.

e-Portfolio showcasing my personal projects.

Sparkify project

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.

An extension that registers all pharmacies in Argentina.

JSON-driven ETL pipeline framework prototype

FleetFluid is a Python library that simplifies data transformation by letting you use AI-powered functions without writing (and hosting) them from scratch.

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.

End To End MLOPS Project With ETL Pipelines- Building Network Security System

End-to-end real-time data engineering pipeline that ingests YouTube API metrics, streams them through Kafka on Google Cloud, processes data with ksqlDB, and delivers analytics to a Telegram bot using Dockerized microservices.