Junior data engineer - Italia
Pubblicato il 15-09-2026 - Cato in Milano
Your mission Bring a tender from the source portal into Cato: scraping, parsing, merging, enrichment. Youll start by owning a handful of sources end to end - the scraper, the job behind it, and the data that comes out - and take on more as you go. Not tickets handed to you: sources youre responsible for.
What youll actually do Build and maintain scrapers for national tender portals, where reading the source in its original language is part of the job. Keep them alive: portals change their HTML, move endpoints, break pagination, throttle you. You find out before the customer does. Turn messy sources into clean records: broken HTML, inconsistent XML, APIs that lie about their own schema. Write and maintain orchestrator flows: retries, backfills, alerting, and a clear answer to "Did todays run actually land?" Work on merge and dedup - the same tender arrives three times, in three shapes, and only one version can reach the customer. Ship AI enrichment steps: batch LLM extraction of requirements, embeddings, OCR on attachments. Guard data quality with tests and checks that fail loudly before a customer finds the gap.
Ideal profile Python that holds up:
typed, tested, and readable six months later. Youve scraped something real:
HTTP, HTML and XML parsing, pagination, sessions, rate limits - and you know why a scraper that worked yesterday is broken this morning. SQL youre comfortable in:
joins, aggregations, window functions. Youll read from the database every day; tuning and running it isnt your job. Builder by default:
you see a manual process and your first instinct is to automate it. Comfortable with messy sources:
broken HTML, inconsistent XML, PDFs that were scans of scans. You close your own loop:
you check that what you shipped actually ran, before someone else has to ask.
Experience 1-2 years writing Python in production: scrapers, ETL scripts, automation - anything that had to run unattended and be fixed when it didnt. Exposure to an orchestrator (Prefect, Airflow, Dagster) is a plus, not a requirement: youll learn ours properly. Exposure to LLM-based extraction is welcome; curiosity about it is mandatory.
What you wont find here No micromanagement: we trust you to own your part of the stack. No "standard" 9-to-5 mentality: we care about outcomes and we are looking for people who are willing to go the extra mile. No "weve always done it this way" excuses: were here to disrupt, not to follow old patterns.
Our Tech Stack Data & Infra: Python, PostgreSQL, Prefect, AWS AI: batch LLM extraction, embeddings, OCR
Compensation RAL €35,000 - €45,000 + equity, depending on profile.
Hiring Manager Lorenzo Rossetto [email protected]