Summary
Dana Kaplan is a Senior Data Engineer in San Francisco with 12 years of experience turning messy, terabyte-scale data into reliable, production-ready assets. She has led ETL and batch ingestion efforts using Spark, Airflow, Snowflake and the AWS ecosystem, built in-house tooling to replace SaaS components, and authored automated QA and lineage systems to keep complex pipelines auditable. Comfortable managing contractors and on-call emergencies alike, she combines hands-on engineering with strong operational discipline and a history of optimizing cost and performance. Early work spans analytics, recommendation systems, and NLP, and she even won a company hackathon applying pretrained neural nets to image-style clustering—evidence of a practical curiosity that drives unexpected, high-value solutions.
12 years of coding experience
11 years of employment as a software developer
Hoodie of Academic Achievement Machine Learning & Data Science, Hoodie of Academic Achievement Machine Learning & Data Science at Galvanize - San Francisco, SoMa
BS BA Mathematics (BS) Economics (BA), BS BA Mathematics (BS) Economics (BA) at University of Rochester