Summary
Aaron Wiegel is a Senior Data Quality Engineer with a PhD in physical chemistry and nine years of hands-on experience building reliable data products and pipelines for biotech and diagnostics companies. He combines rigorous scientific training with practical data engineering—introducing data profiling, automated unit/integration tests in Databricks, and medallion architectures with Snowflake/dbt—to make data trustworthy and production-ready for ML workflows. Aaron has led and mentored small engineering teams, translated lab workflows into denormalized analysis schemas and LIMS integrations, and automated model training and deployment to shrink setup time from hours to minutes. Comfortable across Python, numerical simulation, and cloud tooling, he excels at uniting experimental and observational datasets to surface actionable insights. Outside core engineering, he volunteers as a community college instructor in prison education and shares technical projects on his blog, reflecting a blend of technical depth and unusual cross-disciplinary communication experience.
9 years of coding experience
20 years of employment as a software developer
PhD, Physical Chemistry, Atmospheric Chemistry, PhD, Physical Chemistry, Atmospheric Chemistry at University of California, Berkeley
BS, Chemistry, Technical Japanese, BS, Chemistry, Technical Japanese at University of Wisconsin-Madison
Data Science, Data Science at Metis
English, Japanese