Anshuman Rout

I’m a Data Engineer (ETL & Analytics Engineering) focused on turning complex business and operational data into reliable, analytics-ready systems. With a B.Tech in Computer Science and Engineering, I’ve built a career around automation, data quality, and scalable engineering practices.

At Chubb, I architected and optimized end-to-end ETL/ELT pipelines using Informatica IICS and Azure Data Factory, automating ingestion of insurance datasets into a centralized Snowflake data warehouse. I developed SQL/T-SQL transformations and stored procedures that improved data availability for downstream analytics by 35%, and I used Python and dbt to implement modular Medallion Architecture, transitioning legacy reporting into scalable cloud-native Star Schemas. I also reduced manual reconciliation errors by 20% through automated data validation frameworks and engineered CI/CD workflows for data assets to maintain strong governance in a regulated environment.

My projects reflect the same engineering mindset: resilient workflows and secure integrations. I designed an asynchronous job processing platform with FastAPI and Celery that cut average request latency by 85% and achieved a 99.7% job completion rate under failures, while introducing dead-letter queues that reduced debugging time by 60%. I also built a Stripe-to-QuickBooks Online reconciliation platform with webhook-driven workflows and OAuth-based multi-tenant integrations, eliminating manual reconciliation for 95% of transactions and reducing errors by 78%, with sub-5-minute reconciliation latency.