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Profile

Join date: Jun 17, 2025

About

Scott Vahey is the Director of Technology at Ficstar, where he has spent nearly 20 years designing, scaling, and advancing one of Canada’s most established enterprise web-scraping platforms. With a degree in Computer Software Engineering from the University of Toronto, Scott combines deep technical expertise with hands-on leadership in cloud-based crawling systems, domain-specific languages (DSL), and high-reliability data pipelines. He is widely recognized for his thought leadership on enterprise-scale scraping, clean data standards, and the engineering differences between startup and enterprise use cases. His work ensures Ficstar’s systems remain stable, scalable, and future-ready.

Areas of Expertise:

  • Enterprise-Scale Web Scraping Architecture

  • Cloud-Based Crawling Systems & DSL Design

  • Data Quality, Clean Data Standards & System Reliability

  • Scrum, Agile Leadership & Technical Team Management

  • Large-Scale Automation & Infrastructure Engineering


LinkedIn: https://www.linkedin.com/in/scott-vahey-3032aa88/

Posts (6)

Feb 13, 2026 ∙ 6 min
Case Study: Collecting Electronic Part Prices Across Major Distributors and Online Stores
This case study covers a pricing intelligence project where we at Ficstar, a fully managed web data collection and web scraping services  partner for enterprises, collected electronic component prices across top Distributor, Aggregator and Manufacturer websites to capture the tiered pricing and lead time for each part number. In this project, the client provided a massive input list of 700,000+ electronic parts , and our job was to capture price by quantity (tiered price breaks)  and lead...
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Nov 12, 2025 ∙ 8 min
How We Collected Nationwide Tire Pricing Data for a Leading U.S. Retailer
Through this project, we helped a leading U.S. tire retailer monitor nationwide pricing and shipping data from 20 major competitors, covering over 50,000 SKUs and generating roughly one million pricing rows per weekly crawl. The challenges included add-to-cart pricing, login-required sites, captchas, and multi-seller listings, all of which required adaptive algorithms, caching, and contextual parsing to ensure 99% accuracy. Our QA framework, built around cached validation and regression...
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Oct 2, 2025 ∙ 6 min
How Reliable is Web Scraping? My Honest Take After 20+ Years in the Trenches
In this article, I unpack why accuracy in web scraping is so challenging, how companies often underestimate the problem, and how we at Ficstar Software Inc. have built our entire service model around solving it.
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Scott Vahey

Scott Vahey

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Director of Technology

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