Hybrid Cloud AI Data Architect — Multi-Cloud & FinOps

Vodafone; Madrid; Híbrido; EUR 75.000 - 120.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Hybrid work model

Meal voucher

Descripción de la vacante

Vodafone is seeking a Cloud and AI Data Solutions Architect to lead end-to-end design of secure, scalable data platforms across multi-cloud environments. You will collaborate with cross-functional teams to create modular, reusable components aligned with strategic goals, embedding FinOps and governance into architecture.

The role requires translating business requirements into production-ready AI solutions, bridging stakeholders, engineers, and platform owners, while ensuring security and

Formación

• End-to-end design and architecture of scalable data platforms in hybrid and multi-cloud environments (GCP, AWS, Azure).
• BI pipeline design projects experience.
• In-depth knowledge of data warehousing, data lakes, and ETL/ELT orchestration.
• Strong IaC and cloud security practices.

Responsabilidades

• Understand data and model them inside BI to create value with quality.
• Design and implement AI architectures aligned with Vodafone goals.
• Design data mesh architectures with robust data contracts.
• Ensure scalability, efficiency, and security of cloud/AI solutions.
• Provide high-level effort estimations for cloud migrations.

Conocimientos

ETL development

Cloud migration

Data warehousing

Infrastructure as Code

FinOps

Cloud security

Stakeholder management

Educación

Bachelor’s degree in computer science, engineering and/or other STEM degrees

Cloud certifications

Herramientas

Terraform

BigQuery

Descripción del empleo

Vodafone is seeking a Cloud and AI Data Solutions Architect to lead end-to-end design of secure, scalable data platforms across multi-cloud environments. You will collaborate with cross-functional teams to create modular, reusable components aligned with strategic goals, embedding FinOps and governance into architecture.

The role requires translating business requirements into production-ready AI solutions, bridging stakeholders, engineers, and platform owners, while ensuring security and