Automation & data pipelines.

The unglamorous plumbing that moves your data where it needs to be.

Start a project How I build it
  • n8n
  • ETL / ELT pipelines
  • pandas
  • REST APIs

The problem

Someone on your team moves data by hand every week. It’s slow, it’s easy to get wrong, and it stops the day that person is away.

Here’s how I build it

How I build it.

5 steps from the first conversation to launch. The diagram fills in as each part gets built.

  1. Step 01

    Find the manual work

    We list the jobs someone does by hand every week: the exports, the copy and paste, the report that takes a morning.

  2. Step 02

    Connect the tools

    An n8n workflow links the tools you already pay for through their APIs. It runs on a schedule, or when something happens in one of them.

  3. Step 03

    Collect from the web

    When the data lives on websites, a scraper collects it at scale. It runs at a polite rate and retries, so a slow site doesn’t break the run.

  4. Step 04

    Clean and load

    pandas cleans and reshapes the data before it is stored. Each step retries when it fails and logs what it did.

  5. Step 05

    Report on a schedule

    Excel and CSV reports build themselves from live data and arrive when they’re due. Nobody copies numbers by hand.

What you get.

All of it, or only the part you need. Each piece can be scoped on its own.

Built with

  • n8n
  • ETL / ELT pipelines
  • pandas
  • REST APIs
  1. 01n8n workflows connecting the tools you already pay for
  2. 02ETL / ELT pipelines with scheduling and retries
  3. 03Large-scale scraping and data ingestion
  4. 04Scheduled Excel and CSV reporting off live data

Where I’ve done it.

Quoted from my CV, then the builds you can open and check for yourself.

  • Padelos

    Associate AI Engineer

    Jan 2026 — Present

    • Built n8n pipelines that extract, transform, and report conversation data from Azure Cosmos DB across player and admin schemas.

  • IR Solutions

    Junior AI Engineer

    Jul — Dec 2025

    • Built production agentic AI systems with n8n and engineered large-scale web scraping and data-ingestion pipelines.

Builds.

All projects

Questions clients ask.

Not covered here? Ask me directly.

Why n8n?

It connects to hundreds of tools without custom code, each workflow is visible as a diagram, and it can run on your own server. When a step needs real code, Python does that part.

Will it work with the tools we use?

If a tool has an API or exports files, yes. If it has neither, scraping is often still an option.

What happens when a step fails?

It retries. Every run is logged, so you can see what failed and run it again once the cause is fixed.

Can you collect data from large sites?

Yes. I’ve built large-scale scraping and data-ingestion pipelines. The data is checked before it is stored, so bad rows don’t end up in your reports.

Other services.

Work with me

Have a project like this?

Tell me what you want to build, and I'll tell you how I would approach it.

Let’s talk