I specialize in developing scalable data solutions with expertise in Python, SQL, and cloud technologies. Currently seeking full-time opportunities in Data/Analytics Engineering.
I am committed to continuous learning and professional development
Validated expertise in cloud concepts and AWS services with a focus on security, architecture, and pricing.
Demonstrates ability to implement infrastructure as code using HashiCorp Terraform for reliable deployment.
I specialize in a range of technologies for data engineering and analytics
A selection of my recent data engineering and analytics projects.
Building a modern data pipeline to process Formula 1 racing data using real-time architecture. The system integrates Python for data collection, PostgreSQL for storage, Kafka and Debezium for streaming, and DuckDB with dbt for analytics.
Designed and implemented a comprehensive data pipeline using AWS, Airflow, and Snowflake to process large datasets efficiently.
Insights and tutorials on data engineering, analytics, and technology.
In this article, I share my journey building a data pipeline for Formula 1 racing data using modern technologies. Learn how I leveraged PostgreSQL for storage, Kafka and Debezium for streaming, and DuckDB with dbt for analytics, implementing advanced patterns like CDC and SCD Type 2 along the way.
This tutorial explains how to build a content-based filtering system that predicts user ratings for movies based on their preferences. Learn the fundamentals of recommendation systems, from data preparation to similarity calculation and prediction, with practical Python implementation.
I'm open to new opportunities and collaborations in data analytics engineering. Let's connect and discuss how I can contribute to your team or project.