Przemysław J.

I deliver reliable, analysis-ready web data for consulting, analytics, retail, and ecommerce teams. If you need external data for a project, a business decision, or recurring monitoring, I can turn scattered web sources into a consistent dataset - not just scraping code. Typical projects include: - product catalogs, pricing, promotions, assortment, and availability - seller, ratings, reviews, store, and location data - category trees, taxonomy, identifiers, and SKU counts - cross-matching, normalization, and deduplication across sources - recurring price, assortment, and availability monitoring Ways to work together: - Free feasibility check - I review representative URLs, available fields, and the main limitations, and can prepare a small sample when practical. - Decision-ready dataset - a one-off delivery with agreed fields, normalization, deduplication, QA, and documentation. - Managed data feed - scheduled refreshes with validation, monitoring, and maintenance as websites change. Relevant experience includes multi-source retail pricing for a time-sensitive analysis, store-level assortment datasets across multiple locations, weekly price tracking across approximately 4,000 supplied product URLs, and a long-running daily price feed. Quality is part of the scope. I agree the required fields and checks upfront, document known limitations, and address source or website changes openly. When requirements change, retained source pages may also allow the data to be reprocessed for different fields. Delivery formats include CSV, XLSX, JSON, or another agreed format. I founded DMA Labs in 2016 and remain directly involved in feasibility, scope, delivery, and QA. My Upwork record includes Top Rated Plus status, 100% Job Success, more than $300K in earnings, and 100 jobs. To assess your project, send me 1–3 sample URLs and briefly describe the fields, market, and update frequency you need. I'll review the sources and suggest the next step. Technical capabilities include Python-based web scraping, APIs, GraphQL, JavaScript-heavy websites, data cleaning, normalization, and automated validation.