Data and platform engineer focused on scientific computing infrastructure and distributed systems.

Started in quantitative development (econometrics, statistics, ML), evolved into data engineering and platform infrastructure. Specialized in geospatial data processing, distributed systems, and Linux-based scientific computing environments.

Core areas:

• Data pipeline architecture and orchestration (Airflow, Spark)
• Geospatial data systems (GDAL, PostGIS, NetCDF/HDF5)
• Platform infrastructure and tooling
• Distributed data processing
• Linux system administration and automation
• Scientific computing workflows

Current interests:

• Systems programming (Go, C++, Rust)
• Low-level optimization
• HPC infrastructure
• Game development

Languages: Python, SQL, Bash, C++ (learning), Rust (learning)

Infrastructure: Docker, Linux administration, CI/CD automation, cloud platforms (AWS, GCP)

Data Systems: PostgreSQL/PostGIS, Apache Airflow, Spark, data lake architecture

Specialized: GDAL raster processing, scientific data formats, distributed systems, metadata management

Most work has been in organizational repositories. Portfolio demonstrations coming soon.

Contact: LinkedIn | matias.rebolledo@gmx.es