pstrongYour mission /strong /ppBring 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. /ppbr / /ppstrongWhat you'll actually do /strong /pulliBuild and maintain scrapers for national tender portals, where reading the source in its original language is part of the job. /liliKeep them alive: portals change their HTML, move endpoints, break pagination, throttle you. You find out before the customer does. /liliTurn messy sources into clean records: broken HTML, inconsistent XML, APIs that lie about their own schema. /liliWrite and maintain orchestrator flows: retries, backfills, alerting, and a clear answer to "Did today's run actually land?" /liliWork on merge and dedup - the same tender arrives three times, in three shapes, and only one version can reach the customer. /liliShip AI enrichment steps: batch LLM extraction of requirements, embeddings, OCR on attachments. /liliGuard data quality with tests and checks that fail loudly before a customer finds the gap. /li /ulpbr / /ppstrongIdeal profile /strong /pullistrongPython that holds up: /strong typed, tested, and readable six months later. /lilistrongYou've scraped something real: /strong HTTP, HTML and XML parsing, pagination, sessions, rate limits - and you know why a scraper that worked yesterday is broken this morning. /lilistrongSQL you're comfortable in: /strong joins,



aggregations, window functions. You'll read from the database every day; br / tuning and running it isn't your job. /lilistrongBuilder by default: /strong you see a manual process and your first instinct is to automate it. /lilistrongComfortable with messy sources: /strong broken HTML, inconsistent XML, PDFs that were scans of scans. /lilistrongYou close your own loop: /strong you check that what you shipped actually ran, before someone else has to ask. /li /ulpbr / /ppstrongExperience /strong /pulli1-2 years writing Python in production: scrapers, ETL scripts, automation - anything that had to run unattended and be fixed when it didn't. /liliExposure to an orchestrator (Prefect, Airflow, Dagster) is a plus, not a requirement: you'll learn ours properly. /liliExposure to LLM-based extraction is welcome; br / curiosity about it is mandatory. /li /ulpbr / /ppstrongWhat you won't find here /strong /pulliNo micromanagement: we trust you to own your part of the stack. /liliNo "standard" 9-to-5 mentality: we care about outcomes and we are looking for people who are willing to go the extra mile. /liliNo "we've always done it this way" excuses: we're here to disrupt, not to follow old patterns. /li /ulpbr / /ppstrongOur Tech Stack /strong /pulliData Infra: Python, PostgreSQL, Prefect, AWS /liliAI: batch LLM extraction, embeddings, OCR /li /ulpbr / /ppstrongCompensation /strong /ppRAL €35,000 - €45,000 + equity, depending on profile. /ppbr / /ppstrongHiring Manager /strong /ppLorenzo Rossetto /p

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