Your mission Build and run the pipelines that carry a tender from the source portal to the customers 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 youll 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 todays 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. Idóneo profile Real SQL: you can read an EXPLAIN and say why the plan is bad, not just that it is slow.

Python youd put in production: typed, tested, and readable six months later.

Pipelines youve 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 — youve had to make one fast.

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, K3s/ArgoCD, AWS * AI: batch LLM extraction, embeddings, OCR Compensation RAL €40,000 – €60,000 + equity, depending on seniority and profile.

Hiring Manager Lorenzo

Rossetto [email protected]

📌 Data engineer (Madrid)
🏢 Cato
📍 Madrid