Build and run the pipelines that carry a tender from the source portal to the customer's screen: ingestion, merge, enrichment, delivery. You own concrete pieces of the data pipeline end to end — not tickets handed to you, but the sources, jobs and tables behind them. What you'll actually do

Own scrapers and ingestion for a set of national portals across Spain and Italy, where reading the source in its original language is part of the job. Write and maintain orchestrator flows: retries, backfills, alerting, and a clear answer to "Did today's run actually land?" Work on merge, dedup and reconciliation — 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. Write SQL that survives production: query plans, indexes, JSONB, partitioning, CONCURRENTLY migrations. Guard data quality with tests and checks that fail loudly before a customer finds the gap. Adecuado profile

Real SQL:

you can read an EXPLAIN and say why the plan is bad, not just that it is slow. Python you'd put in production:

typed, tested, and readable six months later.



Pipelines you've actually operated:

with an orchestrator (Prefect, Airflow, Dagster, ArgoWorkflows) and the 3 a.m. failures that come with them. 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. Experience

2–4 years building data pipelines in production. Hands-on with PostgreSQL beyond writing queries — you've had to make one fast. Exposure to LLM-based extraction is welcome; curiosity about it is mandatory. What you won't 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 "we've always done it this way" excuses: we're here to disrupt, not to follow old patterns. AI: batch LLM extraction, embeddings, OCR Compensation

RAL €40,000 – €60,000 + equity, depending on seniority and profile.

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📌 Data engineer (Madrid)
🏢 Cato
📍 Madrid