Andrea Matté

Backend engineer on Smartpricing, the AI-powered RMS inside the Smartness platform (4,000+ properties in Europe).

• Rewrote the core pricing engine that produces all dynamic prices for 4,000+ hotels; migrated gradually with no downtime.
• Built from scratch an event scraping and deduplication pipeline, using geospatial clustering and connected-components graph algorithms to keep stable identifiers across runs.
• Co-developed the competitor price scraper, its APIs, and a ScyllaDB storage layer holding ~300 GB compressed at a ~100x compression ratio.
• Led multiple legacy-to-modern migrations of backends and infrastructure with zero-downtime cutovers.

ScyllaDB-backed storage for scraped competitor prices, designed from the schema up for extreme compression while keeping reads fast for the pricing engine.

• Stores ~300 GB of competitor pricing data at a ~100x compression ratio, serving ~100 QPS to the pricing engine and downstream services.
• Designed the partition and clustering key layout so that the partitions scale horizontally and the rows are compression-friendly. The biggest factor is the custom row format, which is a binary vector-like encoding of the prices.
• Built the ingestion path from the scraper into Scylla via batching, Kafka and stream processing, keeping write amplification low and absorbing bursts.
• Migrated from the old format to the new one, cutting storage by 90%.