Summary
Adam Breindel is an independent consultant and instructor with 12 years of experience architecting distributed data and ML systems, specializing in Apache Spark, Dask, RAPIDS, and probabilistic programming. He has trained and advised engineering teams at major enterprises including Apple, Netflix, Visa, and Qualcomm, and created early industry courseware for Spark 2.x/3.x, Dask, and GPU-accelerated analytics. Beyond teaching, Adam designs proof-of-concept data architectures and has contributed to Databricks and O'Reilly course material and technical reviews, helping bridge academic rigor with production realities. His background in mathematics and classics hints at a rare combination of formal analytical depth and clear, pedagogical communication that clients repeatedly engage for complex decision- and scale-related problems.
11 years of coding experience
Master’s Degree, Classics, 4.0, Master’s Degree, Classics, 4.0 at Brown University
Bachelor’s Degree, Mathematics, 3.91, Bachelor’s Degree, Mathematics, 3.91 at University of Chicago
Post-Baccalaureate, Classics, Post-Baccalaureate, Classics at University of Pennsylvania