Data Engineer_
gabriel_db=# SELECT delivery, result FROM impact;
| delivery | result |
|---|---|
| revenue on the CRM I support | $100M+ |
| monthly data catalog users | 3,000+ |
| legacy SQL and ELT runtime | −80% |
| SAS → Databricks migration | leading |
| governance automations | 10+ |
(5 rows)
I own data products end to end. I design the Lakehouse model, agree data contracts with the teams that consume it and answer for reliability and performance in production.
I designed and shipped a web crawler and 10+ governance automations that remove manual work and keep the data catalog trustworthy for decision makers.
I cut legacy query and ELT/ETL pipeline runtimes by more than 80% with hands-on tuning, on data used by 3,000+ people every month.
Large bank · Wealth Management
I own the data pipelines and Lakehouse models serving the Wealth Management segment. I lead the modernization of legacy SAS routines into Databricks, delivering canonical and derived data layers consumed by the legacy CRM and Salesforce. I design the segmentation logic for Wealth audiences and the data contracts with Salesforce, and productize pipelines end to end: modeling, CI/CD, reliability and monitoring.
Large bank
I architect and manage the core data pipelines of a CRM that sustains a business operation generating R$ 500M+ in revenue. I act as Data Owner of the internal Data Catalog (3,000+ users/month). Optimized SQL/ELT processes by +80% and built a web crawler and 10+ data governance automations with high business impact.
Confidential (NDA)
Autonomous development of ETLs processing millions of daily records. Built pipelines and automations using Python, DBT and DuckDB. Created frameworks to accelerate development, also coding in Node.js, Java and Scala.
Keyrus · Internship
Developed ETL/ELT pipelines and features for a corporate data catalog. Implemented a business glossary, MySQL integrations, and refactored legacy SQL achieving +50% performance gains.
I lead the move of legacy SAS routines to a Databricks Lakehouse serving the Wealth Management segment. I organized the model into canonical and derived layers so the legacy CRM and Salesforce read from the same base.
🎯 Decisions: canonical and derived layers, data contracts with Salesforce, Wealth audience segmentation rules and CI/CD with monitoring on every pipeline.
I design and run the core pipelines of a CRM tied to an operation generating R$ 500M+ in revenue. As Data Owner of the internal data catalog, I answer for the quality and discoverability of data used by 3,000+ people every month.
🎯 Results: legacy SQL and ELT runtimes cut by more than 80%, a web crawler and 10+ governance automations.
End-to-end analytics pipeline for CVM 210 investment funds. Serverless ingestion via AWS Lambda, S3 Data Lake storage and distributed processing in Databricks with Medallion Architecture (Bronze→Silver→Gold).
🎯 Highlight: Automated Medallion Architecture (AWS + Databricks) processing restricted CVM 210 data with Delta Lake (ACID).
Comprehensive AWS Data Lake with Medallion Architecture. Processed 1.1M records via Glue (PySpark), analytical queries in Athena and impact dashboards in Power BI about COVID-19 in Brazil.
🎯 Highlight: Processing of 340+ MB of raw data (1.1M+ records) via AWS Glue (PySpark) and Athena.
Obesity risk prediction (87% accuracy), daily Ibovespa direction (75.76%) and loan default propensity (72%), in Python with Scikit-learn, Optuna, Streamlit and Dash.
Microsoft
2026
Microsoft
2026
Microsoft
2026
Astronomer
Aspire Institute (Harvard Business School)
2025
Astronomer
2025
Astronomer
2025
FIA Business School
Business management, finance and leadership of technology teams.
FIAP
Statistics, predictive modeling and Machine Learning applied to business problems.
FATEC-SP
Software engineering, databases and systems architecture.
📂 db_gabriel
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Open to high-impact challenges in Data Engineering and partnerships in consulting. Shoot me a message!