Data Engineer | Data Governance | AI Applied
I’m a Data Engineer with experience in data integration, automation, and governance in both public and private sectors.
My work focuses on building reliable data pipelines, ensuring data quality, and enabling data-driven decision-making.
Currently working at the Servicio Electoral de Chile (SERVEL), contributing to data governance, interoperability, and institutional data platforms.
- 🔧 Strong background in Python, SQL, ETL pipelines and automation
- ☁️ Experience with Azure, AWS, Docker and CI/CD
- 📊 Focus on Power BI and data visualization for decision-making
- 🏛️ Working with data governance frameworks (MGDE) and public sector interoperability (PISEE, CKAN)
- 🤖 Experience applying AI to document processing, computer vision and data extraction
- ⚙️ Advocate of efficient, maintainable and traceable data systems
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State Interoperability Integration (PISEE – 2025)
Implementation of secure data exchange between government systems under Chile’s Digital Transformation Law (Law 21.180). -
Data Catalog Integration (CKAN – 2025)
Development of institutional data catalog enabling metadata management, traceability and governance. -
Automated Survey Pipeline (2024)
Real-time data visualization using Microsoft Forms + Power BI. -
AI Document Processing Pipeline (2023–2024)
Extraction and structuring of financial and administrative data from PDFs using AI models.
- Python (Pandas, ETL, automation)
- SQL (PostgreSQL, SQL Server, MySQL)
- APIs & Data Pipelines
- Azure DevOps (CI/CD)
- AWS (Serverless, Lambda, ECS)
- Docker
- Power BI
- Grafana, Prometheus ecosystem
- Prefect (workflow orchestration)
- Computer Vision
- Document processing (OCR, LLMs, SLMs)
- Improving my English communication skills
- Deepening knowledge in data governance and scalable architectures
- Building tools around monitoring, data catalogs and observability
“Focused on turning data into reliable systems that support real decisions.”