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Data Engineer

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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

Skills

See also

Data Engineering jobs by country — openings, pay and top skills →

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