Professional Profile
I have spent over 17 years working with database internals, distributed storage, and cloud infrastructure. My career started in database administration (DBA) managing production Oracle, SQL Server, and PostgreSQL environments. That background continues to guide how I design data systems: prioritizing query planner efficiency, storage layout, data integrity, and high availability.
Today, I design and run multi-cloud Lakehouse platforms using Apache Iceberg, Trino, and Dremio across AWS, GCP, and Azure. I handle corporate data modeling across conceptual, logical, and physical stages for both high-concurrency transactional workloads (OLTP) and analytical warehouses (OLAP).
My recent work includes semantic virtualization using OWL ontologies and SPARQL endpoints with Apache Jena Fuseki, building automated batch and streaming pipelines with Apache Airflow and Apache Spark, and implementing data governance and lineage with OpenMetadata.
Whether diagnosing lock contention on national-scale registration systems or designing lakehouse storage for climate observation data, my goal is straightforward: build data platforms that run reliably, scale predictably, and keep operational costs low.
Modern Lakehouse
Open-format analytical storage using Apache Iceberg, Trino, Dremio, and cloud object storage (S3, GCS, ADLS Gen2).
Database Tuning & HA
Deep tuning of PostgreSQL, Oracle, and SQL Server for national concurrency, partitioning, and HA/DR.
Governance & Quality
End-to-end data products, automated lineage, OpenMetadata cataloging, and data contracts.
Semantic Web & AI
OWL ontologies, SPARQL-over-SQL virtualization, Apache Jena Fuseki, and Agentic AI architectures.
Technologies & Skills
Data Engineering & Architecture
Databases & Tuning
Cloud Platforms (AWS • GCP • Azure)
Orchestration & Streaming
Semantic Web & Knowledge Graphs
AI & Agentic Engineering
Languages & Integration
Governance & Observability
DevOps & Infrastructure
Professional History
Database Specialist & Data Architect
Core Responsibilities
- Design and run multi-cloud data platforms across AWS, GCP, and on-premises environments.
- Build and schedule data pipelines using Apache Airflow (MWAA, Cloud Composer) and Apache Spark (Glue, EMR, Dataproc).
- Modernize analytical storage into Lakehouse architectures using Trino, Dremio, and Apache Iceberg on AWS S3 and GCP Cloud Storage.
- Create corporate data models (conceptual, logical, and physical) for transactional and analytical workloads.
- Design semantic metadata layers and knowledge graphs using OWL ontologies, SPARQL, and Apache Jena Fuseki.
- Deploy data catalogs and metadata lineage tracking with OpenMetadata.
Key Achievements & National Initiatives
Designed a hybrid data architecture using PostgreSQL (RDS) for transactional data and Google BigQuery for analytical queries. Developed automated ELT pipelines to ingest beneficiary records and lower query compute costs.
Tuned database configurations and query execution plans for Brazil's centralized university selection portal. Optimized queries, indexes, and table partitions on Oracle and SQL Server to maintain zero downtime during peak registration traffic.
Designed the indicators data model and ingestion pipelines, unifying socio-environmental data from scientific institutes and government ministries into a single analytics warehouse.
Connected distributed relational databases into a federated semantic layer, enabling researchers to run cross-institutional SPARQL queries without centralizing raw data.
Optimized bulk XML and JSON ingestion routines between research institutions and the Integrated Publishing Toolkit (IPT) biodiversity databases, resolving database latency issues during large synchronization runs.
Platform mapping research infrastructure across Brazilian scientific and technological institutions. Led database performance tuning, access security updates, and schema maintenance.
National digital public infrastructure for territorial and environmental data. Led the implementation of an open-source Lakehouse on Apache Iceberg and Trino, making environmental datasets accessible to internal analytics and AI models via APIs.
Data platform supporting Brazil's reporting requirements under Article 13 of the Paris Agreement. Designed the AWS data architecture covering ingestion, relational and analytical stores, cataloging, and API endpoints for AI consumption.
Sustainable urban development initiative by the Ministry of Science, Technology and Innovation (MCTI). Designed the AWS data infrastructure connecting transactional databases, analytical storage, governance, and API access.
DBA SQL Server / Oracle / MySQL & Cloud Data Engineer
Core Responsibilities
- Provided database administration, architecture, and query tuning for enterprise clients at an Azure partner consultancy.
- Maintained and resolved issues across Oracle Database, Microsoft SQL Server, MySQL, and PostgreSQL.
- Planned database cloud migrations and built data lakes on Microsoft Azure.
Key Achievements & Projects
- Cloud Database Migration: Migrated on-premises databases to Azure SQL Database and Azure Database for PostgreSQL/MySQL with minimal maintenance windows.
- Azure Data Engineering: Built automated ETL and ELT pipelines with Azure Data Factory (ADF) and Azure Databricks, landing structured client data into Azure Data Lake Storage Gen2 (ADLS Gen2).
- Performance Rescue: Diagnosed root causes for high CPU usage, lock waits, and I/O bottlenecks in production SQL Server and Oracle databases through query rewrites, index redesigns, and engine parameter tuning.
Core Responsibilities
- Wrote stored procedures, functions, and database integration logic for daily tax calculations in the energy sector.
- Automated data transformation workflows using Python and Oracle PL/SQL.
Key Achievements & Projects
- Tax Processing Speed-up: Refactored long-running PL/SQL packages and trigger routines, cutting hours off daily batch calculation runs.
- Python Automation: Replaced manual file conversions with automated Python scripts to ensure accurate data feeds into federal tax reporting systems.
Core Responsibilities
- Managed the company's core database systems (Oracle DBA), VMware virtual environment, and internal software tools.
- Developed custom business applications in PL/SQL and PHP to integrate with JD Edwards ERP.
Key Achievements & Projects
- VMware Virtualization: Migrated physical bare-metal servers to a virtualized VMware ESXi cluster, cutting hardware costs and enabling automated snapshot backups.
- Oracle JDE ERP Tuning: Tuned SQL queries and database memory parameters for the Oracle database supporting JD Edwards, resolving lockups during end-of-month accounting closures.
- End-to-End Business Intelligence: Modeled the corporate data warehouse and deployed Oracle BI Enterprise Edition (OBIEE) dashboards for executive and plant managers.
- B2B Platform Development: Built the company's first web-based B2B ordering portal from scratch, designing the relational database model and REST APIs to sync orders directly with JD Edwards.
Personal Projects & Open-Source Tools
Developer utilities, database diagnostics, and privacy-focused tools I built and maintain.
SchemaGraphos
Visual database modeling tool. Design ER diagrams in the browser and export schema definitions as clean SQL statements.
Textr
Browser-based private messaging on top of the Nostr protocol. Implements NIP-17/59 Gift Wrap and NIP-44 end-to-end encryption without relay servers reading message content.
Facta
Decentralized reporting application built on the Nostr protocol, allowing users to publish public reports with cryptographic identity verification.
Vocalis
Local, offline speech and English learning assistant developed natively for Linux desktops, with zero telemetry or cloud dependency.
Hookring
Webhook ingestion system with request validation, RabbitMQ queuing, and Linux desktop notifications, built with FastAPI, PostgreSQL, RabbitMQ, and Nginx.
NoCloud Todo
Offline-first task management web app that stores all data locally in the browser with zero cloud synchronization.
NoCloud SQL
In-browser SQL query viewer and formatter with local AI-assisted query explanation, running entirely inside the user's browser without sending queries to a third-party API.
NoCloud MD
Browser-based Markdown and Mermaid editor with live preview, running completely client-side.
Speed Dial Page
Fast, customizable browser home page and dashboard for quick access to developer bookmarks and workflows.
Tools SQL Server
Collection of production-tested T-SQL diagnostic queries for database administrators to inspect index fragmentation, locks, and query plan caches.
Minke
Terminal user interface (TUI) for managing local Docker containers, written in Go.
My Backup
Lightweight Docker container that runs scheduled mysqldump backups against MySQL or MariaDB instances (like AWS RDS) and uploads compressed archives directly to Amazon S3.
Propagatio
Python CLI tool that compares schemas and replicates tables and row data between two PostgreSQL databases.
Education & Certifications
Academic Background
Postgraduate Certificate (Lato Sensu) in Data Science
Database Engineering
Technician in Data Processing
Languages & Details
Certifications & Executive Training
AI & Agentic Engineering
- AI Agent Developer
- Claude Code: Software Engineering with Generative AI Agents
- ChatGPT Advanced Data Analysis
- OpenAI GPTs: Creating Your Own Custom AI Assistants
- Prompt Engineering for ChatGPT
- AI Agents and Agentic AI with Python & Generative AI
- AI Agents and Agentic AI Architecture in Python
AI Fundamentals & Productivity
- AI for App Building
- AI for Data Analysis
- AI for Content Creation
- AI for Writing and Communicating
- AI for Research and Insights
- AI for Brainstorming and Planning
- AI Fundamentals
Databases, Residency & Governance
- PostgreSQL 17: Core Concepts & Advanced SQL Techniques – Coursera (2026)
- PostgreSQL 17: Optimizing Performance & Security – Coursera (2026)
- Mastering PostgreSQL 17 – Coursera (2026)
- ETL and Data Pipelines with Shell, Airflow and Kafka – IBM (2026)
- Data Science Training Program with Technological Residency – CPQD / PUC Campinas (2023)
- SCRUM Foundation Professional Certificate (SFPC) – Scrum Foundation (2011)
- MCTS Microsoft SQL Server Certification – Green Treinamentos / SP (2008)
- Oracle DBA Administrator – Senac / SP (2007)
- Google Cloud Fundamentals: Big Data and Machine Learning
- Microsoft Azure: Fundamentals
- Specialization: Open Source + Azure for Data and Analytics
- Introduction to R: Profa. Luciane Alcoforado & Statistics is with R! team
Let's Discuss Data Architecture
Available for senior architectural roles, mission-critical database consulting, Lakehouse design, and high-impact enterprise collaborations.