17 set - Milano
Cato
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; 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. Experience 1-2 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.Our Tech StackData & Infra: Python, PostgreSQL, Prefect, AWS AI: batch LLM extraction, embeddings, OCRCompensationRAL €35,000 - €45,000 equity, depending on profile.Hiring ManagerLorenzo Rossetto (email hidden)#J-18808-Ljbffr
18 set - Chiavari
Acrobatica
18 set - Fonzaso
Greta
18 set - Trento
Car Clinic
18 set - Nola
Demetra Formazione