Sandish N
Staff Software Engineer (ML, Distributed Systems) at Hewlett Packard Enterprise
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolSandish N is a Staff Software Engineer based in San Francisco with 12+ years building large-scale distributed systems, cloud platforms, and production ML pipelines. He combines deep hands-on expertise in Spark, Kafka, Kubernetes and cloud services (AWS/GCP) with fluency in Java, Scala, and Python to deliver high-performance data infrastructure. A prolific Apache contributor, he led the spark-protobuf integration enabling native Protobuf read/write in Spark and has contributed significant features and fixes to Pinot, Druid, Kudu and NiFi. At HPE and prior roles he architected low-latency data pipelines, IoT cloud-native products, and optimized long-running Spark jobs for real-world PB-scale workloads. He’s results-oriented and pragmatic, equally comfortable debugging thread dumps and designing Helm charts for Kubernetes deployments. Beyond production systems, his work shows a pattern of smoothing integration pain points—serialization, connector tooling, and cloud-native ops—that accelerate team delivery.
11 years of coding experience
7 years of employment as a software developer
Bachelor's Engineering, Computer Science, Bachelor's Engineering, Computer Science at Visvesvaraya Technological University
English, Telugu, Kannada, Tamil
Stackoverflow
312reputation
16kreached
11answers
1question
Github Skills (16)
javas10
big-data10
spark10
protobuffer10
protobuf10
java10
scala9
sql8
apache-spark6
hive6
oracle6
apache-kafka6
spark-streaming6
sqoop6
impala6
Programming languages (5)
Github contributions (5)
apache/spark
Jun 2017 - Nov 2023
Apache Spark - A unified analytics engine for large-scale data processing
Role in this project:
Back-end Developer
Back-end DeveloperContributions:142 reviews, 11 PRs, 158 comments in 6 years 6 months
Contributions summary:Sandish primarily contributed to the Apache Spark project by adding support for Protobuf, a data serialization format. Their work included implementing `from_protobuf` and `to_protobuf` functions, enabling Spark to read and write Protobuf data within data frames. The user also added support for Protobuf imports and validated Protobuf timestamp and duration types. Further, the user improved the project by introducing support for OneOf field and recursive checks.
analyticspythondata-processingsqlapache
SandishKumarHN/incubator-druid
Jun 2019 - Jul 2020
Apache Druid (Incubating) - Column oriented distributed data store ideal for powering interactive applications
Contributions:68 pushes, 7 branches in 1 year 1 month
incubatingidealdata-storeapachebig-data
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