Summary
Matthew Gin is a data engineer with nine years of hands-on experience turning messy, Excel-centric workflows into automated, production-ready pipelines using Python, Airflow, Spark, SQL, and cloud platforms (AWS/GCP). He has a track record of practical automation in insurance and mining contexts—building tools that download carrier reports, generate renewal documents, and migrate legacy VB systems into clean CSV pipelines synchronized to cloud storage. Comfortable across the stack, he combines backend skills (Postgres, Docker) with analytics and visualization (Tableau, Power BI, Plotly) to deliver measurable time savings and reduced error. His engineering roots trace back to tinkering with Arch Linux and low-level programming, which underpin a careful, systems-minded approach to reliability and failure handling. Outside engineering he’s a zen facilitator and avid reader of classical texts, bringing a disciplined, reflective mindset to problem solving and team collaboration. Based in Vancouver, he complements formal training (UBC B.A.Sc. and a Udacity Data Engineering nanodegree) with pragmatic, automation-first solutions that scale recurring business processes.
8 years of coding experience
3 years of employment as a software developer
Bachelor of Applied Science (B.A.Sc.), Chemical and Biological Engineering, Bachelor of Applied Science (B.A.Sc.), Chemical and Biological Engineering at The University of British Columbia
Nanodegree, Data Engineering, Nanodegree, Data Engineering at Udacity
CAVE Employment Program
English, Japanese, French