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Data Engineer (AI Foundations)

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Summary

A data engineer in Madrid building AI-ready data foundations on Google Cloud: designing BigQuery schemas as the source of truth for business units, developing ETL/ELT pipelines to migrate and clean legacy data, and partnering with the AI Office to make data structures ML-ready. Core stack: GCP, BigQuery, SQL, Python.

As a Data Engineer within the Data Department, you will be the "boots on the ground" responsible for building the robust data foundations required for high-impact AI initiatives. Reporting directly to the Head of Data, you will work closely with specific Business Units (BUs) and the AI Office to transform raw legacy data into high-quality, scalable data models within the Google Cloud ecosystem.

Tareas

  • Data Modeling & Warehousing: Design, build, and maintain scalable data schemas in BigQuery that serve as the single source of truth for specific BUs.
  • Pipeline Development: Develop and optimize ETL/ELT processes to migrate and clean data from various BU-specific sources into the centralized GCP environment.
  • AI Readiness: Work alongside the AI Office to ensure data structures (feature sets, historical snapshots) are optimized for machine learning consumption.
  • Stakeholder Collaboration: Act as the technical bridge between the Data Department and BU leads to understand specific business logic and translate it into technical requirements.
  • Data Governance: Implement best practices for data quality, documentation, and lineage to ensure the AI models are built on trustworthy information.
  • Experience: 3-5 years of professional experience in Data Engineering, with a heavy focus on data warehousing and modeling.
  • GCP Ecosystem: Deep hands-on experience with Google Cloud Platform, specifically BigQuery and associated data tools
  • Technical Proficiency: Expert-level SQL and proficiency in Python.
  • Modern Data Stack: Experience with transformation tools and data modeling methodologies (e.g., Star Schema).
  • CommunicationAbility to navigate different Business Units and explain technical constraints to non-technical stakeholders.
  • Opportunity to build AI-ready infrastructure from the ground up.
  • Collaborative environment working directly with leadership and the AI Office.
  • Professional growth in a high-impact role within the Google Cloud ecosystem.

Skills

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See also

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