Summary
Brendan Bailey is an experienced data engineer with a decade of hands-on work applying Python, SQL, and Tableau to make government and civic services more effective. He’s delivered data products across contexts—from predictive workforce models for LAPD recruitment and randomized trials to improve hiring pipelines, to building membership reporting, ETL automation, and a Redshift-based warehouse for the AFL‑CIO. Brendan blends public-sector impact with private-sector scale, currently contributing to data engineering at Meta after leading analytics and innovation efforts for the City of Los Angeles. He holds advanced training in analytics and data science and brings a practical habit of turning policy questions into measurable, production-ready solutions. Notably, his background spans campaign field operations to enterprise data platforms, giving him a rare combination of domain empathy and technical execution.
10 years of coding experience
6 years of employment as a software developer
Data Science Immersive, Data Science Immersive at General Assembly
Master's degree Analytics, Master's degree Analytics at Georgia Institute of Technology
University of California, San Diego