Microsoft Cloud Solution Architect - Data & AI 

Philippines 

985232103

Required/Minimum Qualifications (RQs/MQs)
Bachelor’s degree in computer science, Information Technology, Engineering, Business or related field AND 4+ years’ experience in cloud/infrastructure technologies, information technology (IT) consulting/support, systems administration, network operations, software development/support, technology solutions, practice development, architecture, and/or Business Applications consulting OR equivalent experience.

Additional or Preferred Qualifications (PQs)

• Business Value: The ability to convey the business needs and value of proposed solutions, plans, and risks to stakeholders and decision makers. This includes the ability to persuade and inform based on facts and alignment with goals and strategy.
• Trusted Advisership: The ability to build trusted advisor status and deep relationships across stakeholders (e.g., technical decision makers, business decision makers) through an understanding of customer needs and technologies.
• Situational fluency: Using self-awareness as a mechanism to interpret verbal and non-verbal cues to increase your ability to "read the room."
• Insightful listening: asking insightful questions to understand the customer needs, issues, business environment and drivers, and going beyond what customer has said.

Technical
• Breadth of technical experience and knowledge in foundational security, foundational AI, architecture design, with depth / Subject Matter Expertise in one or more of the following:
o Deep domain expertise in one of the Data-specific areas, such as Azure SQL Data (IaaS/PaaS), Azure Cosmos DB, deployments and migrations to the cloud, Open-source database (PostgreSQL, MYSQL) deployments and migrations, Cloud Scale Analytics (Microsoft Fabric, Power BI), and Data Governance (Microsoft Purview) OR hands-on experience working with the respective products at the expert level.
o Experience creating Data & Analytics Proof of Concepts (PoC), Minimum Viable Products (MVPs) for customers that lead to production deployments.
o Competitive Landscape: Knowledge of key Data & Analytics platforms such as AWS, GCP, Snowflake, etc.
o Software development practices like DevOps and CI/CD tool chains (i.e., Jenkins, Azure Developer Services, GitHub) and container orchestration systems (i.e., Docker, Kubernetes, Cloud Foundry, Azure Kubernetes Service, GitHub).

Customer-Centric Approach:
• Understand customers' overall data estate, business priorities, and IT success measures. Innovate with AI infused analytic solutions that drive business value.
• Prioritize Customer Satisfaction: Foster positive relationships and become a trusted advisor.
• Ensure Solution Excellence: Deliver solutions with high performance, security, scalability, maintainability, repeatability, reusability, and reliability upon deployment. Gather insights from customers and partners.

Business Impact:
• Drive Consumption Growth: Develop opportunities to enhance Customer Success and help customers extract value from their Microsoft investments.
• Unblock Customer Challenges: Leverage subject matter expertise to identify resolutions for customer blockers. Follow best practices and utilize repeatable IP.
• Architect modern Data & Analytics Solutions: Apply technical knowledge to design solutions aligned with business and IT needs. Create modernized Data & Analytics platform solutions with infused AI, lead POCs and MVPs, and ensure long-term technical viability.

Technical Leadership:
• Advocate for Customers: Share insights and best practices, collaborate with the Engineering team to address key blockers, and drive product improvements.
• Continuous Learning: Stay updated on market trends, collaborate with the Data, Analytics and AI technical community, and educate customers about the Azure platform.
• Accelerate Outcomes: Share expertise, contribute to IP creation, and promote reusability to accelerate customer success.