Aditya Raman User

At PROPERO, I build cloud-native data pipelines for Shopify, Meta, Google, and BigQuery analytics. I created a serverless AWS inventory-sync pipeline that processes more than 200,000 SKU records per run with a 99.2% match rate, reducing manual reconciliation time by 41%.

I've optimized Shopify update workflows using GraphQL aliases, chunked bulk mutations, and throttling retry logic, reducing full-sync runtime from roughly 45 minutes to under 12 minutes while cutting API calls by 85%.

I also built a GCP Cloud Run pipeline that ingests Shopify webhooks and Meta Pixel events, transforms and routes them through Signals Gateway into BigQuery. The resulting attribution layer gave a fashion retail client a unified source of truth for paid-channel reporting and self-serve Looker Studio dashboards.

Beyond production pipelines, I engineered a real-time credit-card fraud detection project using Kafka, Databricks Lakeflow, PySpark, Delta Lake, and PostgreSQL. I enjoy building reliable streaming and batch data systems that turn fragmented operational data into analytics-ready insights.