Your missionBring a tender from the source portal into Cato: scraping, parsing, merging, enrichment. You'll 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 you're responsible for.What you'll actually doBuild 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 today's 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 profilePython that holds up: typed, tested, and readable six months later.You've 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 you're comfortable in: joins, aggregations, window functions.



You'll read from the database every day;

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tuning and running it isn't 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.Experience1-2 years writing Python in production: scrapers, ETL scripts, automation - anything that had to run unattended and be fixed when it didn't.Exposure to an orchestrator (Prefect, Airflow, Dagster) is a plus, not a requirement: you'll learn ours properly.Exposure to LLM-based extraction is welcome;

curiosity about it is mandatory.What you won't find hereNo 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 "we've always done it this way" excuses: we're here to disrupt, not to follow old patterns. xlwpduy Our Tech StackData & Infra: Python, PostgreSQL, Prefect, AWSAI: batch LLM extraction, embeddings, OCRCompensationRAL €35,000 - €45,000 + equity, depending on profile.Hiring ManagerLorenzo

📌 Junior Data Engineer - Italia (Roma)
🏢 Cato
📍 Roma