Jeff Boerger
Data Engineer

Jeff Boerger

Data Engineer | Python | SQL | ETL Pipelines | Cloud

CS graduate and entrepreneur building data infrastructure that tells real business stories. I co-founded a chiropractic clinic, made my own role obsolete through systems thinking, and went back to school for Computer Science. Now I build ETL pipelines, interactive dashboards, and Python tools - with real data, deployed to production.

Based in Houston, TX - relocating to Central Florida.


Clinic Revenue Pipeline

A full ETL data engineering pipeline built on 7 years of real revenue data from a chiropractic clinic in Austin, TX. Includes data cleaning, transformation, SQLite database loading, and an interactive Streamlit dashboard.

Theme Park Analytics Pipeline

A real-time data engineering pipeline ingesting hourly ride wait times from Walt Disney World. Built on a production-grade modern stack: Apache Airflow for orchestration, Snowflake as the cloud data warehouse, and dbt for transformations. Includes Orlando weather correlation analysis. Data flows automatically every hour — no manual intervention required.

Resume Keyword Analyzer

Python NLP tool scoring resume-to-job-description alignment using fuzzy string matching and set-based keyword comparison. Supports .txt, .docx, and .pdf uploads and live URL scraping of job postings. Features 1,000+ keywords curated from real 2026 job postings across DE, DA, and SWE roles. Renders the full job description with color-coded highlights — green for keywords you already have, yellow for gaps to add.

SQL Coronavirus Data Exploration

Analyzed a large-scale global Cornonavirus dataset in BigQuery using advanced SQL including window functions for rolling vaccination totals, CTEs, temp tables, and multi-table JOINs to surface death rates, infection percentages, and vaccination progress across 200+ countries.

Google Advanced
Data Analysis Capstone

End-to-end data analysis project on NYC Taxi & Limousine Commission data - performed EDA and data cleaning in Python, built visualization in Tableau, conducted A/B hypothesis testing using scipy, and built a mulitple linear regression model to predict taxi fares. Followed the PACE framework (Plan, Analyze, Construct, Execute) throughout.