Webscrapper
Developing and supporting a customizable engine to collect data from multiple unstructured sources for a leading UK venture capital firm.
Our client is a leading international venture capital firm with offices across Europe, North America, and Asia, investing in high-growth startups from seed funding through Series A.
Challenge
• Automatically track product listings, removals, and price changes across dozens of financial services sites, ensuring real-time data collection and analysis.
• Extract key fields such as bank name, product name, interest rate, min/max investment, notice period, and account type from unstructured web pages.
• Provide a reliable data feed for analytics teams to spot market trends in real time, enabling faster decision-making and data-driven insights.
Solution
Agile Project Management
Led requirements workshops and sprint planning to define the scraper’s scope, cadence, and error-handling policies, ensuring on-time delivery and adherence to professional standards.
Interactive Prototyping
Built UI mockups and data-flow diagrams on Google App Engine, demonstrating how parsed data would be collected, indexed, and exposed via API endpoints, and providing clear insight into system integration and seamless user experience.
Robust Parser Implementation
Developed a Tornado-based parser with comprehensive exception handling, logging failures, retrying transient errors, and alerting on source-structure changes, while ensuring performance optimization and smooth data processing.
Scalable Data Aggregation
Created a custom aggregation engine that normalizes and indexes scraped data providing a simple REST API for nontechnical teams to query and filter market information.
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