Presales Solution Architect - Data & AI

About the Role:

As a Presales Solution Architect Azure Data & AI, you will play a crucial role in designing and implementing data analytics and AI solutions on the Azure platform. You will collaborate with cross-functional teams to gather requirements, design end-to-end solutions, and provide technical guidance to ensure scalable, secure, and high-performing architectures.

Key Responsibility :

• Collaborate with cross-functional teams to gather requirements and design end-to-end data and AI solutions.
• Leverage deep expertise in Azure services (e.g., Azure Synapse Analytics, Azure Data Factory, Azure Databricks, Azure Machine Learning, Microsoft Purview, Fabric, Azure Cognitive Services, Azure OpenAI) to architect robust platforms.
• Design and optimize data models to support reporting, analytics, and business intelligence needs.
• Architect solutions for scalability, performance, and cost-efficiency, considering data volume, query complexity, and user concurrency.
• Define data integration strategies to extract, transform, and load (ETL) data from various sources, ensuring data consistency and quality.
• Implement security measures and best practices to protect sensitive data and ensure compliance with industry standards and regulations.

Preferred candidate profile

• Experience in solution architecture or presales roles, with a focus on data analytics and Azure cloud technologies (no specific years required).
• Extensive hands-on experience with Azure services such as Azure Synapse Analytics, Azure Data Factory, Azure Databricks, Azure Machine Learning, Microsoft Purview, Fabric, Azure Cognitive Services, Azure OpenAI, and Power BI.
• Solid understanding of data modeling, ETL processes, data warehousing, and data governance principles.
• Ability to design secure, scalable, and high-performing architectures.
• Strong communication and stakeholder management skills, with the ability to explain technical concepts to non-technical audiences.
• Work closely withWork closely with data engineers, data scientists, business analysts, and partners to understand needs and provide technical guidance.