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
1 year of employment as a software developer
Senior Secondary School, CBSE 12th grade - 95.8%, Senior Secondary School, CBSE 12th grade - 95.8% at AECS Magnolia Maaruti Public School
Master of Computational Data Science (MCDS), Systems Concentration, 4.0/4.3, Master of Computational Data Science (MCDS), Systems Concentration, 4.0/4.3 at Carnegie Mellon University
Bachelor’s Degree, Computer Engineering, GPA : 9.34/10.0, Bachelor’s Degree, Computer Engineering, GPA : 9.34/10.0 at National Institute of Technology Karnataka
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