The Role
Build and maintain scalable BigQuery data models and ETL/ELT pipelines within Google Cloud. Clean and migrate legacy business-unit data, establish governance and lineage, and optimize datasets for AI and machine learning consumption. Collaborate with business-unit leaders and the AI Office to translate business logic into technical requirements and ensure reliable, high-quality data foundations.
Summary Generated by Built In
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.
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.
Skills Required
- 3-5 years of professional experience in data engineering, focused on data warehousing and modeling
- Deep hands-on experience with Google Cloud Platform, especially BigQuery and associated data tools
- Expert-level SQL proficiency
- Proficiency in Python
- Experience with transformation tools and data modeling methodologies such as Star Schema
- Ability to collaborate across business units and explain technical constraints to non-technical stakeholders
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The Company
What We Do
Weewoo Inc is a Spanish company based in the Canary Islands specializing in the acquisition and improvement of mobile applications and games for iOS and Google Play. They leverage their expertise to help companies optimize their mobile apps and games to better reach and engage millions of users worldwide.
