ABOUT ME

Amazon, India - Data Engineer 2

Languages: Python, Bash, Hive SQL, JS

• Fintech and Tax: Enhancing and building data pipelines to generate monthly, weekly compliance reports and implement new business expansions in all regions.
• Internal Tooling: Developing ETL product with different functionalities such as modeling/report generation/orchestration for Tax audit teams as a self-serving tool.

Microsoft, India - Data & ML Engineer 2

Languages: SQL, Python, Bash

• Windows + Devices: Ingesting and building business-critical metrics for Windows such as MAD/DAD Calculations, OKRs. Understanding business to identify and calculate different cohorts consumed by 28 teams internally to manage their targets.
• Azure Services: Leveraging Azure services. Migrating existing legacy services to Azure using Synapse Analytics, Azure Data Factory.
• Store Personalization: Productionized ML models and implemented new frameworks to train deep-learning models and reduced training costs by 80% using Resilience LPG framework.

Amazon, India - Data Engineer

Languages: SQL, Python, Bash

• Architecture Design: Using Amazon ECS, Fargate, EC2 and S3 designed a scalable solution for ingesting large datasets.
• Data Ingestion: Built Critical Datasets using Redshift for Amazon Logistics (AMZL) and also supported Incremental improvements for existing datasets. Across Amazon, more than 80 Teams use the datasets built for their reporting needs.
• Data Pipeline: To timely deliver the critical datasets to customer clusters, built and optimized processes which resulted in 25% SLA improvement and better data quality.
• Business Support: Worked with Business Users to identify DEA (Delivery Estimate Accuracy) misses in Amazon Indian Logistics process and built datasets to identify the DEA daily for packages.

JPMorgan Chase, India - Associate

Areas: Big Data, Hadoop, BI Reporting | Languages: SQL, Python, Bash

• Business: Delivered Cost-Based Allocation Model for Chase Merchant Services which reduced time for business users to make decisions proactively on managing excess costs.
• Reporting: Built Tableau Dashboards for the Mortgage Banking sector which helped project executives to monitor pipelines. Worked with Alteryx for data blending, wrangling, and creating final extracts. There were 300 Unique daily active users for these dashboards.
• Process Improvement: Worked on optimizing the process execution using Spark SQL by tweaking memory parameters which resulted in 50% Improvement in SLA.
• Operational Excellence: Adopted Autosys for scheduling, Bit Bucket for version controlling to our project. Automated deployment of code using Jenkins into production environments for decreasing operational overhead. Understanding of Big data architecture which includes YARN, Hive, Impala, Spark to resolve high critical issues.

General Electric - Summer Intern

Areas: Machine Learning, NLP | Languages: Python, R

• Vehicle Fault Detection Techniques: Developing algorithms that can detect faults in Vehicle engines using the data of other parameters. Also developed text mining techniques to filter the bad data and find ground truth.

Indian Institute of Technology, Madras

Dual Degree (B.Tech + M.Tech) in Electrical Engineering - Minor in Development Sciences

All India Rank 728 in the IIT Joint Entrance Exam (IIT-JEE), among 560,000 students who appeared in 2012