At PUIG BRASIL, I structured a Lakehouse with Delta Lake, Spark, PySpark, and S3, and developed incremental ingestion and CDC pipelines with Databricks and Kafka. I recovered more than 25,000 records and eliminated redundant writes on unchanged reruns.
I also used Apache Airflow to orchestrate ingestion, processing, and validation, with automations that reduced manual work by 80%. By restructuring processing, I reduced cost and latency by up to 50%.
As a freelance Data Engineer, I developed Python and SQL ETL/ELT pipelines integrating four data sources and processing more than 50,000 records per month. I also automated extraction, transformation, and validation, and created dashboards consolidating 15 financial, commercial, and operational KPIs.
In my projects, I’ve worked on Lakehouse pipelines with Kafka, Spark, and Delta Lake, as well as analytics and machine learning workflows. I’m a three-time Airflow Certified professional, with hands-on experience integrating LLMs and AI agents into data workflows.
