Data Engineer (AI Foundations)

WEEWOO; Madrid; On-site; EUR 70,000 - 100,000; Full time

Job summary

WEEWOO in Madrid is seeking a Data Engineer to build robust data foundations for high-impact AI initiatives. You will transform raw legacy data into scalable data models within the Google Cloud ecosystem, reporting to the Head of Data and collaborating with the AI Office.

In this role you will design data schemas in BigQuery, develop ETL/ELT pipelines, ensure data governance, and communicate with BU leads to translate business needs into technical solutions. 3–5 years experience required.

Qualifications

• 3–5 years of professional experience in Data Engineering.
• Strong data warehousing and modeling experience.
• Hands-on experience with Google Cloud Platform (BigQuery).

Responsibilities

• Design, build, and maintain scalable data schemas in BigQuery.
• Develop ETL/ELT pipelines to centralize data from BU sources.
• Collaborate with BU leads and AI Office to prepare AI-ready data.
• Implement data governance, documentation, and data lineage.

Skills

BigQuery

SQL

Python

Data Warehousing

Data Modeling

GCP

Job description

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).
• Communication:Ability 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.