Robert Zacchigna
Lead Software Engineer at State Farm
New Lenox, Illinois, United States
Summary
👤
Senior🎓
Top SchoolRobert Zacchigna is a software and data engineer with eight years of experience building cloud-native, high-performance data architectures for the financial services sector. He combines a Master's in Data Science with hands-on expertise in AWS, Kubernetes, Spark, Snowflake and Airflow to design scalable ETL pipelines, event-driven microservices, and cost-efficient orchestration systems. At Capital One and Discover he modernized legacy workflows into containerized, distributed solutions that improved throughput and reduced operational costs while maintaining strict compliance. Now at State Farm, he continues to blend ML curiosity with engineering rigor, favoring reusable Python libraries and automated CI/CD to accelerate delivery. Colleagues rely on him for pragmatic architecture decisions that bridge data science models and production-grade systems.
9 years of coding experience
9 years of employment as a software developer
Masters of Science, Data Science, Masters of Science, Data Science at Bellevue UniversityBachelors in Information Technology, Systems Analyst/Development, Bachelors in Information Technology, Systems Analyst/Development at Illinois State University
Github Skills (33)
stock10
api-client10
python9
defaults8
prediction-model8
mkvmerge8
monitoring7
master-detail7
jupyter-notebook7
dedicated-server6
media-library6
jekyll5
snapshots5
matroska5
machine-learning5
Programming languages (7)
Github contributions (5)
Robert-Zacchigna/MKVAudioSubsDefaulter
Apr 2024 - May 2026
Simple multi-processing python cli to set the default audio and/or subtitles of a single matroska (.mkv) file or a library of files WITHOUT having to remux the file
Contributions:11 releases, 2 PRs, 39 pushes in 2 years
audioautomationclidefaultsmatroska
Robert-Zacchigna/robert-zacchigna.github.io
Dec 2021 - Apr 2025
Personal site of data science related projects ranging from data analysis and exploration to machine learning and prediction models (mostly using Jupyter Notebook).
Contributions:1 PR, 54 pushes in 3 years 4 months
data-analysisdata-sciencejupyter-notebookmachine-learningprediction-model
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