Data Solution Architect en Madrid, España

Job Overview

Capgemini Global Insights & Data business line is a market leader in data, platform and analytics across many sectors, offering end‑to‑end data integration to cloud platform, AI engineering capabilities and sector‑based advanced analytics solutions.

Your Role

The Data Solution Architect designs, implements and optimizes data‑driven solutions that empower organisations to make informed decisions. The role bridges business requirements and technical execution, ensuring robust, scalable data architectures aligned with strategic objectives.

Responsibilities

• Develop comprehensive data architectures and solutions that address business needs, integrating diverse data sources and platforms.
• Collaborate with stakeholders to translate business requirements into technical specifications.
• Expertise in data modelling, relational and non‑relational databases, and cloud data platforms (e.g., Azure, AWS, Google Cloud).
• Create comprehensive solution architectures that integrate data architecture, technology and databases for optimal performance and scalability.
• Work closely with stakeholders to translate business requirements into technical solutions.
• Develop architecture designs for cloud‑based services, including PaaS and App Services.
• Proficiency in data integration tools, ETL frameworks and big data technologies (e.g., Spark, Hadoop).
• Implement data governance frameworks in alignment with ITIL standards and best practices.
• Oversee the development and implementation of data integration strategies across different systems and platforms.
• Excellent communication and presentation abilities.
• Strong problem‑solving skills and a collaborative mindset.
• Ability to manage multiple projects and priorities in a fast‑paced environment.

Skills and Experience

• Data pipeline: expertise in designing and managing data pipelines across diverse cloud environments.
• Bachelor's degree in data science, analytics, business or related field. Advanced degrees or certifications are a plus.
• Certifications in cloud architecture or data engineering (e.g., AWS Certified Solutions Architect, Google Professional Data Engineer).
• Experience with machine learning, advanced analytics or business intelligence platforms.
• Familiarity with agile methodologies and DevOps practices.
• Data architecture: deep knowledge of IT databases, data structures and architecture principles.
• Databases: proficiency in SQL and NoSQL databases.