Data Engineer (AI Foundations)

Join; Madrid; Presencial; EUR 45.000 - 70.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Competitive salary

Modern tools

Growth in AI/Google Cloud

Descripción de la vacante

Join is seeking a Data Engineer within the Data Department to build robust data foundations for AI initiatives on Google Cloud. You will report to the Head of Data and collaborate with BUs and the AI Office to transform raw data into high-quality, scalable models.

You will design BigQuery schemas, develop ETL/ELT pipelines, and ensure data governance while enabling ML readiness. This hands-on role offers growth in a cloud-first environment.

Formación

• 3–5 years of professional data engineering experience.
• Deep hands-on experience with Google Cloud Platform, BigQuery.
• Expert-level SQL and proficiency in Python.
• Experience with the Modern Data Stack and star schema.
• Strong communication to bridge BU and technical teams.

Responsabilidades

• 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 into the centralized GCP environment.
• AI Readiness: Work with the AI Office to ensure data structures are optimized for ML consumption.
• Stakeholder Collaboration: Act as the technical bridge between the Data Department and BU leads.
• Data Governance: Implement data quality, documentation, and lineage practices.

Conocimientos

Data modeling

SQL

Python

ETL/ELT

Data warehousing

Communication

Herramientas

BigQuery

Google Cloud Platform

Descripción del empleo

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.

Beneficios

• 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.