Anil Batchu
Staff Software Engineer at The Apache Software Foundation
Cupertino, California, United States
Summary
👤
Senior🎓
Top SchoolAnil Batchu is a Staff Software Engineer in Cupertino with 12 years of experience building large-scale Big Data systems and data platforms, currently driving engineering work at Apple Media Products. He combines deep backend expertise in distributed data processing (Spark, Kafka, Hadoop, Cassandra) with hands-on experience migrating on-prem clusters to AWS EMR and building orchestration and ETL frameworks. A long-time contributor and committer to Apache Drill, he has implemented storage plugins (Mongo, Kafka) and BSON/record reader improvements that materially boosted query capabilities in a well-known open-source MPP query engine. Prior roles at Intuit, PayPal and Walmart highlight a track record of designing production data services—graph analytics, real-time replication, and stream processing—across high-throughput environments. He holds an M.Tech from IIT Kharagpur and an M.Sc in Applied Mathematics, bringing rigorous analytical training to complex engineering problems. Colleagues describe him as a pragmatic architect who prefers shipping resilient, observable systems over theoretical perfection.
12 years of coding experience
13 years of employment as a software developer
M.Sc Applied Mathematics, M.Sc Applied Mathematics at University of HyderabadM.Tech Computer Science, M.Tech Computer Science at Indian Institute of Technology, Kharagpur
Github Skills (14)
drilldown10
javas10
big-data10
bson10
java10
apache-drill10
hadoop9
sql9
kafka9
hive8
mongodb-database8
mongodb8
jdbc7
parquet7
Programming languages (2)
Github contributions (5)
apache/drill
Apr 2014 - Nov 2017
Apache Drill is a distributed MPP query layer for self describing data
Role in this project:
Back-end Developer
Back-end DeveloperContributions:7 commits, 3 PRs, 34 comments in 3 years 7 months
Contributions summary:Anil primarily contributed to enhancing the Apache Drill backend, focusing on improving data processing capabilities. Their work involved enabling null handling within the HiveRecordReader, fixing null handling in the REST interface, and addressing performance issues in the Mongo Storage Plugin. Furthermore, the user implemented features related to the Kafka storage plugin and improved the BSON reader for more efficient data retrieval.
jdbcdatastreambig-datadatabasehadoop
akumarb2010/drill
Aug 2016 - Nov 2017
Contributions:58 pushes in 1 year 3 months
drilljavaapache-drillapache
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