---
title: "Gokul Ganesan - Senior Software Engineer in Bengaluru | Tal"
description: "Meet Gokul Ganesan, Senior Backend Engineer | Building and Operating Production Geospatial Pipelines | Spatial Observability based in Bengaluru. AI stack includes anthropic apis, claude code, and claude. Explore public work links including github and gokulg.in."
image: "https://tal.club/meet/gokul-ganesan/share-image"
---

# Gokul Ganesan on Tal

## Headline

Senior Backend Engineer \| Building and Operating Production Geospatial Pipelines \| Spatial Observability

## About

Almost a decade of experience building production geospatial systems processing PetaBytes of satellite imagery and Earth observation data\. Expert in large\-scale spatial data pipelines, real\-time geospatial analytics, and cloud architecture for remote sensing applications across climate monitoring, agricultural technology, environmental compliance, and geospatial search systems\. Proven track record delivering PetaByte\-scale imagery warehouses, sub\-50ms geospatial transformations, and 75% reductions in satellite data preparation time\. M\.Tech Remote Sensing & GIS from Indian Institute of Remote Sensing, currently building next\-generation sustainability data systems at Sagri\.

## Location

Bengaluru

## AI stack

anthropic apis

claude code

claude

codex

openai

openclaw

## Work experience

Senior Software Engineer at Sagri Co\., Ltd, Nov 2024 \- Present · 1 yr 11 mos, Bengaluru, Karnataka, India, Senior Geospatial Data Engineer \- Value Chain Carbon Removal Systems • Building value chain carbon removal estimation pipelines using ROTHC carbon sequestration models and Dead Organic Matter decomposition analysis across corporate agricultural value chains • Architecting cloud\-native MRV infrastructure on AWS for automated monitoring, reporting, and verification of carbon removals throughout enterprise value chain operations • Engineering Zarr\-based data processing systems for multi\-dimensional environmental datasets enabling real\-time carbon removal quantification across distributed value chain locations • Developing end\-to\-end sustainability analytics platform integrating satellite imagery, soil data, and climate models to deliver value chain carbon removal insights for corporate environmental reporting

Software Engineer III at Turing, Oct 2022 \- Oct 2024 · 2 yrs 1 mo, India, \- Engineered high\-scale data ingestion infrastructure processing 3M\+ developer profiles daily using TypeScript and Google Pub/Sub, achieving 84x performance improvement \(14 hours → 10 minutes\) \- Architected unified data platform consolidating mission\-critical datasets from multiple sources \(spreadsheets, databases, SalesForce\) into single source of truth dashboard \- Built enterprise dashboard using TypeScript \(NestJs\), MySQL, BigQuery integration deployed on GKE, reducing client conflict resolution from weeks to days \- Delivered 10%\+ gross revenue recovery through automated data standardization and dispute prevention systems \- Orchestrated weekly release cycles enabling rapid iteration and feedback loops for data platform improvements

software engineer II at EagleView, Jan 2020 \- Oct 2022 · 2 yrs 10 mos, Greater Bengaluru Area, \- Built Imagery warehouse to extract, transform and load 20 year corpus of billions of aerial images in the order of PetaBytes \- Used micro\-services architecture to make the ingestion and extraction of the images seamless while reducing the cost per image fetch \- Developing RESTful/gRPC API endpoints to communicate with customers \(REST\)and between the services \(gRPC\) \- Working towards reducing the storage cost of the big corpus of imagery data by making the storage as efficient as possible in AWS S3 using better compression\. \- Developed services which can transform the raw pixels into a geospatially accurate dataset on the fly within 50 ms per tile\.

Geographic Information Systems Engineer at CropIn Technology, Jan 2019 \- Jan 2020 · 1 yr 1 mo, Greater Bengaluru Area, \- Building a Data processing pipeline in AWS which is able to process terabytes of satellite data efficiently and reduce the data preparation time by 75% \- Deploying an automatic scheduler using Apache Airflow which will schedule jobs based on a predefined schedule reducing the manual effort to run the jobs by 90% \- Setting up a Restful API using AWS lambda and API\-gateway to deliver the AI & ML model outputs at scale to the end user with the least amount of human platform monitoring/maintenance possible and as an added benefit this reduced the cost of running the API by 99% \(traffic is less than 1M requests per month\) \- Building a data rendering engine to render both vector and raster data on to web using tileserver\-gl, tippecanoe, GDAL and Rasterio

Engineer \- Search at Mapbox, Jul 2017 \- Dec 2018 · 1 yr 6 mos, Bengaluru Area, India, \- Built a Data specification/workflow customised for mapbox search to normalise all the external vendor data before benchmarking it for quality \- Deployed the data updates and repairs every week after quality benchmarking into multi region production stacks serving close to 1 billion requests a day without any service interruption \- Built a vandalism prevention pipeline for crowd sourced data to prevent malformed or abusive data from entering into the production servers \- Developed a data benchmarking pipeline for different kinds of vector data from point addresses to zipcodes to places to states to countries which helped mapbox to develop a data model which is customised and optimised specifically for mapbox\. \- Improved the data testing environment to get better insights about data coverage based on both data quantity and quality\. \- Built a robust pipeline powered by AWS lambdas and AWS kinesis stream to handle the constant inflow of data from the community driven crowd sourced endpoints like wikidata, OSM, OpenAddresses etc \- Built a backend data pipeline which can Ingest 400M data points and do a series of transformations \(including cleaning, scoring, common data model conversion, QA etc\) reliably at scale using various AWS cloud based infrastructure within a couple of hours\. \- Maintained all the mission critical infrastructures which handled the loading, transforming and serving the data to mapbox search product\.

Data Analyst at Mapbox, Nov 2016 \- Jul 2017 · 9 mos, Bengaluru, Karnataka, India, \- Improved and maintained the underlying spatial data which powers all Mapbox products\. \- Handled the user feedback towards possible map inaccuracies including but not limited to missing features, incorrect tags and vandalisms using a machine learning model to filter out 95% of the all spam \- Improving and repairing base\-data layer without violating the service\-level\-agreement \. \- Created custom filters to filter out all the noisy unwanted data before it reaches the production data foundation and in turn prevent them from rendered on to the maps

## Education

Master of Technology \(M\.Tech\.\), Remote Sensing and GIS, Indian Institute of Remote Sensing

Bachelor of Technology \(B\.Tech\.\), Geology/Earth Science, General, Bharathidasan University

## Public links

- github: https://github\.com/fa7c0n
- gokulg\.in: https://gokulg\.in/

[View the original profile](https://tal.club/meet/gokul-ganesan)

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