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.

Requisitos 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). Communication :Ability to navigate different Business Units and explain technical constraints to non-technical stakeholders.

Ventajas 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. Competitive salary and modern tools.

📌 IT Data Architect (Madrid)
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📍 Madrid