The role
- Build data pipelines: integrate diverse sources (HTML, CSV, relational databases, embeddings) using scalable ETLs.
- Modeling and optimization: design analytical models to generate KPIs and efficiently manage large data volumes.
- Enable AI: prepare datasets for ML, LLMs, and RAG systems, integrating AI for natural language queries.
- DataOps and scalability: apply CI/CD, continuous monitoring, and optimize infrastructure.
- Learn as much as you want about the world of alternative investment.

What we're looking for
- Results-oriented with strong technical ownership.
- Around 3-4 years of experience.
- Relevant experience with SQL / PL-SQL
- Relevant experience with Python (pandas, Pyspark) and Apache spark




- Relevant experience with ETLs & E/R models
- Relevant experience working with Data & Development teams
- Experience with AWS services (EMR, Lambdas,…) or similar Cloud
- Fluency in Spanish and English

This gives extra points
- Basic experience with data science environments
- Basic experience with Vector database and with scraping engines
- Work with multi-country and multi-source data.
- Experience working in with financial data

What we offer
- 25 days of vacation (and your birthday off)
- Hybrid mode: 2 days in office 3 days in remote

📌 Data Engineer (Madrid)
🏢 mscope
📍 Madrid