Automated E-Commerce Retail Arbitrage & Catalog Feed Engine
Automated spreadsheet processing, margin calculation, and headless catalog upload pipeline for high-volume retail arbitrage sellers.
Problem Statement & High-Level Architecture
Developed automated data pipelines that parse supplier inventory manifests, calculate net profit margins and ROI across marketplaces, and headlessly upload verified product catalogs to enterprise retail arbitrage manager dashboards.
Engineering Design & Data Pipeline
Engineered with Python, Openpyxl, and automated HTTP/REST session workers. Features automated file deduplication, custom margin formulas, and resilient multipart form-data uploads.
Platform Features & Technical Capabilities
Automated parsing and validation of thousands of supplier product rows in real-time
Dynamic profit margin, tax, and marketplace fee deduction algorithms
Headless batch file uploader directly into enterprise arbitrage dashboards
Automated error isolation flagging mismatched ASINs and discontinued inventory
Engineering Bottlenecks & Architectural Solutions
Supplier manifests often contain inconsistent headers, trailing whitespace, and corrupted pricing formats that break upload parsers.
- Supplier manifests with malformed price strings, missing SKUs, and trailing whitespace.
- High calculation latency when evaluating arbitrage margins across multi-million row catalogs.
- Rapid inventory depletion causing order cancellations on out-of-stock items.
Built an automated pre-flight sanitizer using Openpyxl and Pandas that normalizes columns, validates pricing types, and strips invalid characters prior to transmission.
- Automated pre-flight data sanitizer utilizing Openpyxl and Pandas to normalize schemas.
- Optimized indexed database indices with Redis caching delivering sub-10ms margin lookups.
- Automated delta synchronizer refreshing inventory availability at 15-minute intervals.