Niharika Dutta
Senior Software Engineer at Confluent
Seattle, Washington, United States
Summary
🤩
Rockstar🎓
Top SchoolNiharika Dutta is a Senior Software Engineer with a decade of experience building low-latency, high-performance distributed systems for cloud analytics and ML workloads. She has driven GPU acceleration and Apache Spark integrations at Microsoft—delivering up to 10x speedups on optimal jobs—and recently joined Confluent to continue shaping large-scale streaming infrastructure. Her work on .NET for Apache Spark (including Pandas UDFs, Column.Apply(), and Row serialization) highlights a strong open-source footprint that improves developer productivity for C# data engineers. She combines systems-level performance tuning (cluster pooling, pipeline parallelization) with practical reliability improvements, having raised test coverage to 95% and slashed pipeline queuing time by orders of magnitude. Based in Seattle, she brings a research-informed approach from prior robotics and protocol work to solve production challenges across cloud, data, and distributed compute.
10 years of coding experience
10 years of employment as a software developer
Bachelor of Engineering (B.E.), Computer Science, Bachelor of Engineering (B.E.), Computer Science at Thapar Institute of Engineering & TechnologyMaster’s Degree, Computer Science, Master’s Degree, Computer Science at Ira A. Fulton Schools of Engineering at Arizona State UniversityDelhi Public School- Navi Mumbai
Stackoverflow
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Github Skills (13)
net10
asp-net10
dataframes10
apache-spark10
dotnet10
csharp10
dataframe10
dotnet-core10
dotnet-new9
pandas9
machine-learning8
big-data8
analytics7
Programming languages (8)
Github contributions (5)
dotnet/spark
Sep 2019 - May 2022
.NET for Apache® Spark™ makes Apache Spark™ easily accessible to .NET developers.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:1 release, 258 reviews, 36 commits in 2 years 9 months
Contributions summary:Niharika primarily contributed to the .NET for Apache Spark project by implementing features and making documentation updates. They introduced Pandas UDFs for TPCH queries, enhancing query performance and functionality. The user also exposed the Column.Apply() API, expanding the capabilities of column operations. Furthermore, they added support for Row type serialization/deserialization and exposed the CreateDataFrame API.
emrfsharpmicrosofttpchbigdata
Niharikadutta/docs
Jan 2020 - Apr 2021
This repository contains .NET Documentation.
Contributions:113 pushes, 8 branches in 1 year 3 months
dotnetcsharpdotnet-core
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