Pablo Díaz is a Data Engineer with 9 years of experience building high-performance, production data pipelines and distributed execution platforms. Rooted in an electronics and computer vision background, he transitioned from embedded C++ and image processing to architecting auto-scalable data workflows using Airflow, Rust/C and Python at biotech companies. He has a track record of improving reliability, memory usage and execution speed by designing internal pipeline frameworks, containerized on-demand processing on AWS, and exposing services as REST/Celery tasks. At Biome Makers he focuses on making pipelines easy to author, debug and scale; at uBiome he optimized bioinformatics throughput with custom native libraries. Comfortable spanning low-level systems and cloud-native design, he combines instrumentation savvy with pragmatic software engineering to solve complex data-processing problems. Based in Santiago, Chile, he brings a hands-on, efficiency-first approach and a history of turning research-grade processing into reliable production systems.
9 years of coding experience
7 years of employment as a software developer
Ingeniería Civil Electrónica, Control Automático e Instrumentación, Ingeniería Civil Electrónica, Control Automático e Instrumentación at Universidad Técnica Federico Santa María
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