Dushyant Kumar

Software Engineer

Bengaluru, Karnataka, India6 yrs 6 mos experience
Most Likely To SwitchHighly Stable

Key Highlights

  • Co-founded a low latency logging system for Hadoop.
  • Redesigned data pipelines for GDPR compliance.
  • Achieved significant optimization in Hadoop job execution.
Stackforce AI infers this person is a Big Data and Cloud Services expert with strong software development skills.

Contact

dushyant@cse.iitk.ac.inLinkedIn

Skills

Core Skills

Big DataData ProcessingHadoop

Other Skills

AlgorithmsApache SparkAzkabanC (Programming Language)Cloud ServicesComputer NetworkingComputer VisionConvolutional Neural Networks (CNN)Data ScienceData StructuresDatabase Management System (DBMS)Deep LearningFramework DevelopmentFunctional ProgrammingGDPR Compliance

About

Software developer with the experience of working on big data technologies and distributed systems.

Experience

Linkedin

4 roles

Staff Software Engineer

Promoted

Oct 2024 – Present · 1 yr 5 mos

Sr. Software Engineer

Oct 2021 – Sep 2024 · 2 yrs 11 mos

Software Engineer

Jul 2019 – Sep 2021 · 2 yrs 2 mos

  • Worked as a part of Big Data Org:
  • 1. Co-founded a low latency project, fault-tolerant, scalable, reliable system aims to provide the Hadoop NameNode, yarn ResourceManager, Hive Metastore, etc. logs in a consumable format near real time (latency of few seconds). Several products internally leverage these low latency logs to serve the customers faster.
  • 2. Worked on the GDPR Compliance and data privacy.
  • Redesign the pipeline to process anonymized data.
  • Migrating the pipeline on cloud service which involves redesigning various components.
  • Make the pipeline more scalable to handle data growth without violating SLA.
  • Enable pipeline to support new dataset formats.
HadoopBig DataGDPR ComplianceCloud ServicesData ProcessingScalability

Software Development Intern

May 2018 – Jul 2018 · 2 mos · Bengaluru Area, India

  • Worked on the TuneIN framework: a framework that automatically tune Hadoop jobs to save cluster resources. Did the POC on optimization of execution time of hadoop jobs via this framework. Achieved overall 25-35% improvement in execution time.
HadoopOptimizationFramework Development

Education

Indian Institute of Technology, Kanpur

Bachelor of Technology — Computer Science

Jan 2015 – Jan 2019

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