Rishabh Rustogi

About Rishabh Rustogi

I love building things. I remember, as a kid, the Internet was booming and certain websites were gaining popularity. I thought to myself “Why not make a website of my own?”. That\'s what got me into coding and inspired me to pursue computer science. As a software developer, I like designing applications, debugging programs, and optimizing code. I am thrilled by challenging problems and love to use my knowledge of Data Structures and Algorithms to tackle them. Creating software solutions using custom Deep Learning models is a specialty of mine. Thus, automating manual tasks using the disruptive power of machine learning is something that excites me and helps me to put my knowledge to use. I am interested in finding patterns in complex data and utilizing this intricate behavior to build things that were previously thought to be nearly impossible. I believe in the concept of collaborative thinking and love working in a team. Knowledge to me is the fuel for driving innovation. Thus, my constant thirst to learn got me to Carnegie Mellon as a graduate student to pursue a Master of Information Systems Management. Currently, I am working at Amazon as a Data Engineer to up-skill myself. Languages: Python (w/ Flask, PyTorch, TensorFlow), JAVA, C++, Golang, C, JavaScript, PHP Cloud Technologies: AWS (EC2, RDS, Cloud Formation, Redshift, etc), GCP (Functions, Cloud Runs, VM’s, Storage, etc)Databases & Big Data: NoSQL (MongoDB), SQL (Oracle, MySQL), Hadoop (w/ Hive, HBase, Spark)Systems: Data Structures & Algorithms, Bash Scripting, Linux, GIT, REST web API, AutomationML Skillset: Machine Learning (Linear regression, Decision Trees, SVM, Random Forest, etc), Deep Learning, Causal Inference

Experience

1. Data Engineer Ii

   Amazon

   Dec 2024 — Present · Seattle, WA, US

   Led a zero-downtime migration of ~2.6k production workflows from legacy S3/SWF to S3 + Glue and Airflow; built custom Airflow operators and DynamoDB-backed dynamic DAGs, authored rollback/runbooks, and delivered 0 SLA breaches• Implemented a distributed validation service (partitioned workers via AWS SWF/Lambda) with schema-drift, row-count, and business checksum comparators; processed 20 years of history for 2.5k+ feeds in <5h with alerting and audit trail• Built an ops framework (web UI and SDK) on AWS (Lambda, Airflow, Redshift, DynamoDB, IAM) serving ~2.6K workflows; delivered metadata-driven backfill and deprecation workflows with monitoring and alerts, reducing on-call time from 5 hours to 30 minutes and completing 400+ production runs• Shipped a policy-as-code engine enforcing GDPR RTBF, DMA/DSA, per-feed retention, and IAM-based access over a 140- TB lake; exposed erasure/retention APIs and published versioned feed-level KPIs, saving ~6 hours weekly

Education

• Carnegie Mellon University

  Master of Science - MS, Information Systems Management - Business Intelligence and Data Analytics

• Shiv Nadar University

  Bachelor of Technology, Computer Science

  2016 — 2020

• University of California, Berkeley

  Bachelor of Technology - BTech, Computer Science

  2019 — 2019