Guilherme Santos

I’m a Senior Data Engineer with 4+ years designing and operating enterprise-scale Lakehouse platforms on Azure and Databricks, delivering end-to-end automation in regulated financial environments. I combine strong ETL/pipeline engineering with REST API development and full CI/CD deployment to make data reliable, governed, and usable. I’ve also published applied deep learning research (2024) and I’m currently pursuing an M.Eng. focused on signal processing and computer vision.

At BRQ Digital Solutions, I led the greenfield build of a centralized cloud Lakehouse for non-financial KPIs at one of Latin America’s largest banks. I designed and operated batch pipelines with Databricks (PySpark), Python, and Azure Data Factory, reducing manual reporting effort by ~60% through pipeline automation and data consolidation across 8+ business domains. I implemented Medallion Architecture with data quality validation, governance standards, and CI/CD workflows using Git and GitHub Actions, and I built REST APIs and optimized Delta Lake data models for analytical consumption.

Previously at LexisNexis Risk Solutions, I progressed from Data Engineer I to III (ETL & Pipeline Engineering), taking on pipeline architecture ownership, cross-team technical support, and junior mentoring. I engineered production ingestion pipelines processing ~3–4TB across 8 sources, led storage/performance optimization for a strategic client in the Brazilian credit bureau sector (tables up to 12TB; ~80TB data lake), and reclaimed ~15% of disk capacity via deduplication—addressing recurring 100% disk saturation incidents. I also delivered LGPD-mandated data removal and workflow adaptations for alphanumeric CNPJ identifiers, and served as a cross-team resource for ETL diagnosis and root-cause analysis.