
Data Engineering
Luiz has worked in various industries, including retail, eCommerce, financial operations, sales, and real estate in Brazil.
His expertise includes text processing, sentiment analysis, and infrastructure design. Luiz has optimized ETLs, improved queries, and PySpark code, and implemented table partitioning. He has a proven track record of implementing innovative solutions, such as a StableDiffusion-based application for image enhancement and an XGBoost model for predicting buyer visit-scheduling probability.




Implement a cluster using Kubernetes (GKE) to orchestrate dockerized ETLs in Python.
Creation of a scalable development platform used for several engagements using Jupyter Hub hosted in a cluster with Kubernetes.
Development of a workshop on data science, machine learning models, and their applications.
Implement a supervised model to predict sales of new products based on historical data and visual characteristics, with direct development on the whole machine learning chain, from data processing to serving the model through a REST API using Flask.
Establishment of a workflow to analyze and compare machine learning models using MLFlow.
Engineering excellence
Luiz’s overall performance in a 90-minute live technical assessment ranks in the top 5% of vetted Data Engineerings at Proxify.
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