Arvind Krishnan is a software engineer with a decade of experience focused on systems, distributed computing, and high-performance data processing. Currently building Photon, Databricks' native vectorized execution engine for Spark SQL, he brings hands-on expertise in query performance and runtime optimization. His background blends academic research in consensus algorithms and blockchains with production experience at AWS Redshift where his caching work improved some TPC-DS query runtimes by up to 54%. A CMU MCDS graduate with top-tier undergraduate credentials from NITK, he has also taught database systems and built end-to-end prototypes—from smart-contract-backed mobile apps to analytics dashboards. Comfortable moving between research and production, he’s known for squeezing efficiency out of systems and unifying fragmented codebases. Outside core engineering, he has a track record of translating theoretical distributed-systems ideas into practical improvements in real products.
10 years of coding experience
5 years of employment as a software developer
Senior Secondary School, Senior Secondary School at AECS Magnolia Maaruti Public School
Master of Computational Data Science (MCDS) Systems Concentration, Master of Computational Data Science (MCDS) Systems Concentration at Carnegie Mellon University
Bachelor’s Degree Computer Engineering, Bachelor’s Degree Computer Engineering at National Institute of Technology Karnataka
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