Joaquín Casanova is a Lead Data Engineer with a decade of experience building data platforms and decision systems that power ML-driven products across startups and enterprises. With a physics background from UNAM, he combines rigorous quantitative thinking with hands-on MLOps—designing real-time and batch ML services, ELT pipelines, and robust data quality monitoring using tools like dbt, Fivetran, Snowflake/Redshift, Airflow and FastAPI. He has led data infrastructure initiatives at Atrato and Rappi that process millions of events, emphasizing reliability, CI/CD, and scalable orchestration. Comfortable across backend development, IoT projects, and multithreaded scraping, Joaquín is as likely to optimize a model deployment as he is to architect the ingestion layer that feeds it. Based in Zapopan, Mexico, he brings an experimental scientist’s curiosity to production-grade systems, enabling faster product iteration and measurable business impact.
Contributions:17 pushes, 1 branch in 3 years 1 month
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