- Databricks

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,…)
- 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 - Renowned Company - Travel Required

We are looking for talented Data Engineers with a passion for big-data technologies and building robust data solutions that support advanced analytics.

This is an opportunity to work with modern data technologies, solve complex technical challenges and collaborate with both technical teams and clients.

Key Responsibilities
- Design and build scalable data solutions for advanced analytics.
- Develop and maintain data pipelines and data processing solutions.
- Work with large and complex datasets.
- Apply big-data technologies to solve technical and analytical challenges.
- Develop efficient and reliable solutions using modern programming languages.
- Work with techno

📌 Senior Data Engineer (Madrid)
🏢 Igeneris
📍 Madrid