VARSHITH V HEGDE

Software Engineer

Bengaluru, Karnataka, India2 yrs 2 mos experience

Highly Stable

Key Highlights

Reduced processing time by 40× for data loading.
Built automation tools that cut manual effort by 50%.
Architected cost-effective AWS cloud solutions.

Stackforce AI infers this person is a Backend and Cloud Engineer specializing in scalable systems and cloud infrastructure.

Contact

Skills

Core Skills

Python (programming Language)Rust (programming Language)AwsReact.js

Other Skills

Cloud ComputingFlaskSocket.IOPyQtEC2S3LambdaAmazon Web Services (AWS)JavaGitNode.jsNext.jsTypeScriptresendsupabase

About

I’m a Backend and Cloud Engineer with 2+ years of hands-on experience building scalable, high-performance systems and distributed data pipelines. I specialize in designing and developing backend solutions using Python and Rust, with a strong focus on performance optimization, automation, and cloud infrastructure (AWS). My passion lies in solving complex engineering problems whether that’s reducing processing time by 40×, automating large-scale workflows, or architecting robust cloud solutions that are cost-effective and reliable. On GitHub, I contribute to projects that showcase my work in backend services, automation tools, and data-driven systems: 👉 https://github.com/Varshithvhegde On Dev.to, I share insights, tutorials, and technical deep dives on backend development, cloud patterns, and performance optimization: 👉 https://dev.to/varshithvhegde/

Experience

Kpit

3 roles

Software Engineer

Promoted

Jan 2025 – Present · 1 yr 2 mos · On-site

Developed a full-stack data analysis platform with Python & Rust backends and a PyQt5 frontend, visualizing data from 10+ ego-vehicle and multi-sensor inputs.
Rewrote the ASAM MDF (.mf4) parser in Rust, reducing file load time from ~8 minutes to ~12 seconds (40× performance improvement) while efficiently handling GB-scale datasets.
Built 2+ end-to-end automation tools for annotation teams, reducing manual effort by ~50% and significantly accelerating dataset preparation workflows.
Designed and implemented 3+ high-accuracy geospatial utilities (GPS visualization, distance measurement, intersection detection) using Playwright, OpenStreetMap, and satellite imagery, improving localization validation accuracy.
Led the Cloud Infrastructure initiative, architecting a secure AWS cross-account data transfer system enabling 100% automated data movement between two isolated environments.
Developed an automated AWS data pipeline using EC2, S3, and Lambda to preprocess TB-scale datasets, reducing storage and processing costs by ~30%.
Built a browser-based interface using React, Flask, and Socket.IO, enabling remote filtering and bulk conversion of 1,000+ files per run with real-time visualization.

Python (Programming Language)Rust (Programming Language)AWSCloud ComputingFlaskReact.js+2