Innovative Data Engineer

I specialize in engineering scalable web crawlers using Rust, capable of handling millions of pages with ease. My approach turns raw data into actionable intelligence with cutting-edge technologies.

View my CV for more details.

Async framework for data extraction

capp-rs

Modular framework for async web crawlers and data pipelines

CETD implementation

dom-content-extraction

Content extraction via Text Density algorithm in Rust

Probabilistic data structures

probabilistic-rs

Probabilistic data structures with persistence

Exoplanets Catalog

exoplanets-catalog

Interactive catalog for NASA Exoplanet Archive, built with Leptos, Axum, and Polars

Page analysis for AI agents

pageinfo-rs

Web page analysis tool for AI agents — extracts structure, metadata, and URL patterns

Terminal screen savers

tarts

Terminal screen savers and visual effects in Rust

I build high-performance web crawlers and data pipelines in Rust, capable of fetching millions of pages and API endpoints daily. Combined with Python for flexible processing, these systems deliver clean, structured data at scale.

Web Crawling at Scale: Distributed crawlers handling millions of pages daily with minimal infrastructure footprint, built on Rust for speed and reliability.
Single-View Data Systems: Consolidating data from multiple sources into a unified, comprehensive view — breaking down silos and providing a single source of truth for decision-making and analytics.
Agent Harness Infrastructure: Building the execution environment that wraps AI models with tools, APIs, and memory — giving them the "hands and eyes" to browse the web, interact with services, and run complex workflows autonomously using LLM reasoning.
Empowering AI Systems: Delivering the structured data and tooling that power domain-specific AI solutions, from predictive analytics to natural language processing.