Experienced Data Engineer with 6+ years designing and implementing scalable cloud data solutions on Google Cloud Platform. Specialized in building enterprise-grade data pipelines, MLOps infrastructure, and data architectures. Passionate about engineering excellence, automation, and generative AI applications.
- Data Engineering: Design and optimize ETL/ELT pipelines at scale. Expertise with BigQuery, Dataflow, Cloud Composer (Airflow), and data orchestration.
- Cloud Architecture: Cloud migration, GCP project design, Infrastructure as Code (Terraform), security governance, and cost optimization.
- MLOps & Automation: Vertex AI integration, model versioning, CI/CD pipelines, Python library development, and automated model deployment.
- Data Governance: Model governance, dataset versioning, data quality monitoring, drift detection, and compliance frameworks.
- Enterprise Integration: Lead complex data integration projects across multiple sources (APIs, databases, data warehouses). Neo4j graph database expertise.
- Advanced RAG Systems: Building production-grade retrieval-augmented generation architectures with LLMs
- Prompt Engineering: Optimizing LLM interactions for data engineering tasks and documentation queries
- Data Mesh Architectures: Designing decentralized data platforms for enterprise scalability
- MLOps Best Practices: Establishing governance frameworks for enterprise ML workflows
- Engineering Standards: Creating reusable patterns and documentation for data engineering excellence
| Project | Description | Impact |
|---|---|---|
| Engineering Standards | Comprehensive guide covering Python development practices, GCP architecture patterns, CI/CD, testing, and security for data engineering teams | Reference architecture for engineers |
Years ago, I was a teenager in Venezuela reading every electronic magazine I could find and lurking in IRC channels on Dalnet, absorbing everything about technology. Fast forward through counter-strike tournaments at cyber cafes with friends, LAN competitions, and paintball matches in the Viper League—that curiosity never faded. It just evolved. Now I channel that same passion for exploration into designing scalable data systems and experimenting with the cutting edge of AI.
The search for knowledge never ends. Still following the white rabbit 🐇
Cloud & Data Platforms:
Languages & Core:
Data Tools & Frameworks:
Infrastructure & DevOps:
Databases & Data Modeling:
Open to collaboration and knowledge sharing. Most repositories are organized for learning and professional reference.