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

#J-18808-Ljbffr

📌 Data Engineer (Madrid)
🏢 mscope
📍 Madrid