mabansal
Summary
👤
SeniorMayank Bansal is a Principal Engineer with over 9 years building and scaling compute and data infrastructure for large tech companies, currently focused on perception at Waymo after leading core data infrastructure at Uber. He is an Apache committer and long-time contributor to Oozie, Hadoop MapReduce and YARN, and has architected large-scale data pipelines that process terabytes daily using Hadoop, Pig, Hive and HBase. Mayank’s career spans Yahoo, eBay, and Uber where he combined deep systems expertise with production-focused optimizations for distributed and parallel processing. Known for blending hands-on engineering with platform leadership, he has repeatedly driven reliability and throughput improvements in mission-critical clusters. Based in San Jose, he brings a practitioner’s command of algorithms, performance tuning, and workflow orchestration that isn’t obvious from job titles alone.
9 years of coding experience
Github Skills (9)
stateless10
batch10
utilization10
remote-server10
scheduler9
raft9
apache-spark9
scheduling8
docker4
Programming languages (2)
Github contributions (3)
uber/RemoteShuffleService
Oct 2020 - Jan 2023
Remote shuffle service for Apache Spark to store shuffle data on remote servers.
Contributions:15 reviews, 61 commits, 54 PRs in 2 years 3 months
apache-sparkremote-server
uber/peloton
Jan 2017 - Sep 2019
Unified Resource Scheduler to co-schedule mixed types of workloads such as batch, stateless and stateful jobs in a single cluster for better resource utilization.
Contributions:153 commits, 3 comments in 2 years 8 months
statelessschedulingbatchutilizationworkloads
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