Shruti Mantri
Staff Software Engineer at Google
Bengaluru, Karnataka, India
Summary
🤩
Rockstar🎓
Top SchoolShruti Mantri is a Staff Software Engineer based in Bengaluru with 11 years of experience building large-scale data platforms and developer-facing services across companies like Google, Twitter, Amazon and Moveworks. She brings deep expertise in data pipeline orchestration, distributed systems and platform migrations—having led the India launch of Amazon Restaurants and provided Airflow-as-a-service at Twitter. A hands-on engineering manager and IC, she balances leadership with contributor-level work, including documentation and integration contributions to notable open-source projects such as Kestra (workflow automation) and Mage AI (data pipeline connectors). Comfortable across backend systems, streaming sources (ActiveMQ, RabbitMQ, Kafka) and data stores (Apache Pinot), she has a proven track record of turning complex data infrastructure into reliable, production-ready services.
11 years of coding experience
14 years of employment as a software developer
B.E. (Hons.), Computer Science, B.E. (Hons.), Computer Science at BITS Pilani - Goa Campus
Github Skills (27)
data-pipelines10
python10
data-warehouse10
data-engineering10
workflow-engine10
java10
rabbitmq10
etl10
javas10
datamart10
orchestra10
data-pipeline10
data-integration10
activemq10
documentation10
Programming languages (11)
Github contributions (5)
kestra-io/kestra
Dec 2023 - Mar 2025
:zap: Workflow Automation Platform. Orchestrate & Schedule code in any language, run anywhere, 500+ plugins. Alternative to Zapier, Rundeck, Camunda, Airflow...
Role in this project:
Backend Developer
Backend DeveloperContributions:5 reviews, 32 PRs, 12 comments in 1 year 4 months
Contributions summary:Shruti primarily focused on documentation improvements, specifically correcting and clarifying documentation across multiple flow types such as `EachParallel`, `EachSequential` and `Dag`. They also contributed to documentation corrections for core models and tasks, including the `Schedule` trigger and the `WorkingDirectory` task. Further contributions included examples updates to reflect plugin name changes and standardizing example naming conventions.
pythondataschedulerdata-integritymonitoring
mage-ai/mage-ai
Nov 2023 - Dec 2023
🧙 Build, run, and manage data pipelines for integrating and transforming data.
Role in this project:Data Engineer
Data EngineerContributions:6 reviews, 11 PRs, 4 comments in 1 month
Contributions summary:Shruti primarily contributed to the integration of new data sources and sinks within the Mage AI platform. Their work included adding support for Apache Pinot as a data loader and the addition of ActiveMQ and RabbitMQ as streaming data sources/sinks. The user also made adjustments to existing data integration templates, such as the Kafka loader, indicating an understanding of data pipeline orchestration and data warehousing technologies. Furthermore, the user demonstrates the ability to apply their knowledge of the infrastructure required by data sources and sinks for optimal performance.
pythondatadbttransformationdata-quality
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.