Matt Nelson is a Data Platform Engineer and founder with a decade of experience building AI-native data platforms and LLM-in-the-loop products that let a single engineer operate at the output of a team. He’s rebuilt enterprise stacks from zero—designing and running Snowflake/dbt-based analytics at Canlin and a Dagster/Polars/DuckDB USA data platform processing 1.4B+ mart rows at StackDX—while also shipping frontends and production Claude Code toolchains. Comfortable bridging C-suite strategy and hands-on delivery, he has owned corporate reserves reporting at $1B+ E&P firms and mentored ICs into data roles. His Twochannel side project demonstrates his thesis in miniature: a 16k-product catalog and recommendation system maintained largely via agentic LLM pipelines. Matt holds an MIDS from UC Berkeley and a BASc in Chemical Engineering, and targets senior data/AI leadership or staff engineering roles at companies marrying physical operations with AI at scale.
10 years of coding experience
13 years of employment as a software developer
Master’s Degree, Master of Information and Data Science, Master’s Degree, Master of Information and Data Science at UC Berkeley School of Information
Bachelor of Applied Science (B.A.Sc.), Chemical Engineering, Bachelor of Applied Science (B.A.Sc.), Chemical Engineering at University of Waterloo
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Matt Nelson - Developer at Stack Technologies Ltd.