I build systems that bridge data and software engineering, turning analytical insights into production-grade decision systems.
My work goes beyond traditional data pipelines. I design and implement microservices, APIs, and data platforms that enable real-time processing, automation, and observability.
- Decision Automation: Transforming data into automated business actions
- Data Engineering: Scalable pipelines and lakehouse architectures on GCP
- Backend Engineering: Python microservices with clean architecture principles
- Observability: Distributed tracing and monitoring with OpenTelemetry & Datadog
Background in Business Intelligence, bringing strong context from data consumption to data production.
Data should not only be analyzed — it should be executed.
- Software-to-Data mindset
- Event-driven and distributed systems
- End-to-End ownership (ingestion → decision)
- Systems designed for reliability and scale
Languages
Python · Go · TypeScript · SQL
Data & Cloud
GCP (BigQuery, Dataflow, Pub/Sub) · Airflow · Data Modeling · Lakehouse
Software Engineering
APIs · Microservices · Hexagonal Architecture · DDD · CI/CD
Observability
OpenTelemetry · Datadog
| Project | Description |
|---|---|
| api-to-dataframe | Transform APIs into structured datasets with schema validation and intelligent typing |
| currency-quote | Decision-oriented microservice using clean architecture and strong testing practices |
| open-o11y-wrapper | OpenTelemetry abstraction for traces, metrics, and logs |
| data-pipeline-sync-ingest | Production-grade data pipeline with GCP and orchestration |
| apibrasil-py | Python SDK for APIBrasil integration |
I share practical insights on data engineering, software design, and system architecture on Medium.
Open to:
- Data platform and architecture discussions
- Backend + Data system design
- Open source contributions
- Building data-driven products
⭐ If you find my work useful, consider starring the projects.