Freelance · Data & Backend Engineer
Freelance Python developer building data pipelines, backend tools, and automation.
Pipelines, scrapers, backend APIs, and AI-agent tools, built to run in production.
What I do for you
From messy data to working software
Clear, well-scoped work.
Make your data usable
Pull data from different sources and turn it into one clean, reliable dataset you can actually work with.
Collect data from the web
Automatically gather prices, product info, or listings spread across websites, delivered as a clean file.
Automate manual work
That repetitive task someone does by hand every week? I turn it into a script that runs itself.
Build the tool you need
A custom Python service, an API, or a small internal tool built around your specific process.
Put AI to work on a task
Custom AI-agent tools for a specific job, where the model makes the decisions and tested code does the reliable work.
Work
MCP tools for AI agents
A set of MCP servers that give AI agents reliable access to real, messy data. All published on PyPI and listed in the official MCP registry. The idea throughout: the model decides what it wants, tested code does the actual reading, so values are never guessed.
excel-agent-mcp
Lets an agent read real messy Excel files: multiple sheets, auto-detects the header row
under title rows, forward-fills merged cells. pip install excel-agent-mcp
pdf-agent-mcp
Pulls text and tables out of PDFs (invoices, reports) as clean rows instead of a flattened
blob. pip install pdf-agent-mcp
agentic-csv-cleaner
Cleans messy CSVs where the LLM only picks which cleaning steps to run and tested code does
the transforms. pip install agentic-csv-cleaner
Other projects
Real-Time Market-Data Platform
Real-time ingestion → storage → OHLCV aggregation → live dashboard, with analytics (volatility, anomaly detection). Idempotent, tested, Dockerized.
Product-Catalog Scraper
Dependency-light scraper: pagination, retry/backoff, polite rate-limiting, clean CSV output. Adaptable to any site.
ML Validation Pipeline
Honest out-of-sample validation (NumPy): walk-forward, permutation nulls, to check whether a result is real or just noise.
Tax Valuation Engine
Country-neutral core plus per-jurisdiction plugins, exact decimal math, swappable price source, tested. (Domain: crypto tax, NL box 3.)
About
Lab background, now in code
Before software, I spent six years in molecular diagnostics labs: sequencing, assay validation, and work under GMP. That's where I got careful with data: check it, reproduce it, don't trust a number you can't back up. I work in data and backend engineering now, and the lab background means I understand the domain as well as the code.
Have a project?
Tell me about it
Briefly describe what you need, and I'll reply on whether and how I can help. Small, well-scoped jobs are welcome.