Summary
Bailey Bjornstad is a Data Engineer and Analyst based in Denver with nine years of experience turning mathematical rigor into production-grade data platforms and analytics. They specialize in end-to-end data workflows—collection, transformation, warehousing, and visualization—using Python, SQL, Azure, and PowerBI, and have built reusable tooling (pyunum) for high-throughput Google Trends ingestion. At unumAI they accelerated data collection with asynchronous requests and Azure Functions, enabling low-cost, scalable research and applied political/health analytics for clients including hospitals and state agencies. Bailey pairs a strong mathematics background and academic research experience with practical engineering: comfortable authoring APIs, DAX, and automated pipelines for non-programmer users. They thrive in small, fast-moving teams, translating domain-specific problems into transparent, extensible data products. Motivated by sustainability and social impact, they focus on creating flexible tools that make complex analyses accessible.
9 years of coding experience
1 year of employment as a software developer
High School Diploma, High School Diploma at Pacific Ridge School
Certificate, Data Modeling/Warehousing and Database Administration, Post-undergraduate Study, Certificate, Data Modeling/Warehousing and Database Administration, Post-undergraduate Study at Flatiron School
Bachelor’s Degree, Mathematics, Bachelor’s Degree, Mathematics at Northwestern University
English, Spanish