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About the role
As a Presales Solution Architect focusing on Azure Data & AI, your role is crucial in designing and implementing data analytics and AI solutions on the Azure platform. You will work closely with cross-functional teams to gather requirements, design end-to-end solutions, and offer technical guidance to ensure scalable, secure, and high-performing architectures. Key Responsibilities: - Collaborate with cross-functional teams to gather requirements and design end-to-end data and AI solutions. - Utilize deep expertise in Azure services such as Azure Synapse Analytics, Azure Data Factory, Azure Databricks, Azure Machine Learning, Microsoft Purview, Fabric, Azure Cognitive Services, and 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, taking into account data volume, query complexity, and user concurrency. - Define data integration strategies for ETL processes to extract, transform, and load data from various sources, ensuring data consistency and quality. - Implement security measures and best practices to safeguard sensitive data and ensure compliance with industry standards and regulations. Qualifications Required: - Experience in solution architecture or presales roles, with a focus on data analytics and Azure cloud technologies. - Hands-on experience with Azure services like 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, capable of explaining technical concepts to non-technical audiences. - Collaboration with data engineers, data scientists, business analysts, and partners to understand needs and offer technical guidance. In addition to the Job Responsibilities and Qualifications, please provide any additional details about the company if available. As a Presales Solution Architect focusing on Azure Data & AI, your role is crucial in designing and implementing data analytics and AI solutions on the Azure platform. You will work closely with cross-functional teams to gather requirements, design end-to-end solutions, and offer technical guidance to ensure scalable, secure, and high-performing architectures. Key Responsibilities: - Collaborate with cross-functional teams to gather requirements and design end-to-end data and AI solutions. - Utilize deep expertise in Azure services such as Azure Synapse Analytics, Azure Data Factory, Azure Databricks, Azure Machine Learning, Microsoft Purview, Fabric, Azure Cognitive Services, and 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, taking into account data volume, query complexity, and user concurrency. - Define data integration strategies for ETL processes to extract, transform, and load data from various sources, ensuring data consistency and quality. - Implement security measures and best practices to safeguard sensitive data and ensure compliance with industry standards and regulations. Qualifications Required: - Experience in solution architecture or presales roles, with a focus on data analytics and Azure cloud technologies. - Hands-on experience with Azure services like 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, capable of explaining technical concepts to non-technical audiences. - Collaboration with data engineers, data scientists, business analysts, and partners to understand needs and offer technical guidance. In addition to the Job Responsibilities and Qualifications, please provide any additional details about the company if available.