Data Engineer - AI-Ready Pipelines & DataOps (Hybrid)

mscope

Madrid

Híbrido

EUR 48.000 - 68.000

Jornada completa

hace 25 horas
Sé de los primeros/as/es en solicitar esta vacante
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Ventajas ofrecidas por este puesto de trabajo

25 days vacation
Birthday off!

Descripción de la vacante

mscope is seeking a data engineer to build scalable data pipelines that integrate HTML, CSV, databases and embeddings. You will design models for KPIs and handle large data volumes in a fast-paced environment.

You'll prepare datasets for ML, LLMs and RAG systems, enabling AI-powered natural language queries. The role also emphasizes DataOps, CI/CD, monitoring and infrastructure optimization within a hybrid Madrid office.

Formación

  • 3-4 years of experience in data engineering or related field.
  • Experience with SQL/PL-SQL.
  • Experience with Python (pandas) and Apache Spark.
  • Experience with ETLs and ER models.
  • Experience working with Data & Development teams.
  • Experience with AWS services (EMR, Lambda) or similar Cloud.
  • Fluency in Spanish and English.

Responsabilidades

  • Build data pipelines integrating HTML, CSV, databases and embeddings using scalable ETLs.
  • Design analytical models to generate KPIs and manage large data volumes.
  • Prepare datasets for ML, LLMs and RAG systems, enabling AI for natural language queries.
  • Apply CI/CD, monitoring and optimize DataOps infrastructure.
  • Learn about the world of alternative investment.

Conocimientos

SQL/PL-SQL
Python (pandas)
PySpark
Apache Spark
ETL pipelines
Data modeling
AWS (EMR/Lambda)
Spanish/English bilingual
Data integration

Herramientas

Vector database
Scraping engines
Hadoop/AWS tooling

Descripción del empleo

mscope is seeking a data engineer to build scalable data pipelines that integrate HTML, CSV, databases and embeddings. You will design models for KPIs and handle large data volumes in a fast-paced environment.

You'll prepare datasets for ML, LLMs and RAG systems, enabling AI-powered natural language queries. The role also emphasizes DataOps, CI/CD, monitoring and infrastructure optimization within a hybrid Madrid office.

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