Padma Chitturi is an engineering leader specializing in platform and data infrastructure with 12+ years of experience building production-grade ML and data platforms across enterprises like Indeed, Expedia Group, and Uber. A gold medalist and author of "Apache Spark for Data Science Cookbook," she blends deep hands-on expertise in Spark, streaming, and feature stores with strategic leadership that scaled teams and services across US, APAC, and Japan. At Indeed she led a 25+ member distributed organization to deliver self-serve MLOps, low-latency feature stores, and GenAI inference innovations that cut deployment times from weeks to days. Her early open-source contributions to Apache Storm and engineering work tuning Spark internals reflect a sustained commitment to performance and operational reliability. Known for hiring and coaching strong engineering teams, she pairs technical depth with product-minded delivery—often surfacing practical trade-offs that make complex ML systems maintainable at scale. Based in Bengaluru, she currently leads multiple platform charters focused on database reliability and data infrastructure at Uber.
12 years of coding experience
13 years of employment as a software developer
Jawaharlal Nehru Technological University Hyderabad
SSC Maths Science Social Hindi English Telugu, SSC Maths Science Social Hindi English Telugu at St. Francis De Sales High School
Intermediate Maths Physics Chemistry, Intermediate Maths Physics Chemistry at Gowtham Junior College of Intermediate, Vijayawada
Contributions summary:Padma primarily contributed to the Apache Storm project by modifying command-line scripts related to the `config_value` functionality. They added support for retrieving configuration values for various Storm daemons, specifically focusing on updating the `bin/storm.cmd` and `bin/storm-config.cmd` files to incorporate this feature. These changes involved using the `config_value` command to fetch options related to child processes and modify their parameters within Storm, enabling the dynamic setting of environment variables for these processes.
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