I’m a Data Engineer with experience building end‑to‑end data pipelines, automation tools, and data validation systems. I love solving problems with clean architecture, scalable pipelines, and efficient SQL/Python code.
- 🇵🇾 Based in Paraguay
- 👨💻 Data Engineer at Núcleo S.A. (Telecom & Telefonía Internacional)
- 🔄 Part of the Ingestas Team, responsible for migrating on‑premise PostgreSQL databases to BigQuery
- 🛠️ Familiar with GCP ecosystem, especially BigQuery, Airflow, Data Fusion
- 🤖 Strong background in Python automation, SQL optimization, and ETL/ELT processes
- 📊 Built full validation frameworks, dashboards, and ingestion workflows
- 🔍 Passionate about data modeling, pipeline reliability, and analytics engineering
A completely automated validation pipeline integrated into Airflow’s daily ingestion DAGS. Once each table is migrated from on‑prem PostgreSQL to BigQuery, this validator runs four validation stages:
- Row Counts Validation
- Numeric Sum Validation
- Date Range Validation
- Null Checks
📌 Highlights:
- Parameterized design using metadata tables in BigQuery
- Fully modeled and implemented from scratch (tables, logic, pipeline)
- CI/CD workflow with GitLab (branches, dev → prod deployments)
- Validation results stored in structured BigQuery tables
- Results visualized in Looker Studio, with dashboards I designed
- Python
- SQL (PostgreSQL, BigQuery SQL)
- Bash
- Google Cloud Platform (BigQuery, Cloud Composer/Airflow, Data Fusion)
- CI/CD with GitLab
- ETL/ELT pipelines
- Data Modeling
- Airflow DAG development
- Git & GitLab
- Looker Studio
- Docker
- Linux (Arch-based distros, Ubuntu)
- Neovim / VS Code
- More advanced Data Engineering patterns
- Spark & distributed processing
- Cloud architecture practices
- AWS fundamentals
- Rust
- Email: [email protected]
Thanks for visiting my profile! Feel free to explore my repositories or reach out if you want to collaborate 🤝