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Cloud Solution Architect – Data & AI
- Understand customers’ overall data estate Business and IT priorities and success measures to design Data & Analytics solutions that drive business value.
- Apply technical knowledge to architect and design solutions that meet business and IT needs, create Data & Analytics roadmaps, drive POCs and MVPs, and ensure long term technical viability of new deployments, infusing key AI technologies where appropriate.
- Ensure that solution exhibits high levels of performance, security, scalability, maintainability, repeatability, appropriate reusability, and reliability upon deployment
- Be the Voice of Customer to share insights and best practices, connect with Engineering team to remove key blockers and drive product improvements
- Maintain technical skills and knowledge, keeping up to date with market trends and competitive insights; collaborate and share with the Data & Analytics technical community while educating customers on Azure platform
- Bachelor’s Degree in Computer Science, Information Technology, Engineering, Business, or related field
- 8+ years of experience in cloud/infrastructure technologies, information technology consulting/support, systems administration, network operations, software development/support, technology solutions, practice development, architecture, and/or consulting
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Additional or Preferred Qualifications :
- Master’s Degree in Computer Science, Information Technology, Engineering, Business, or related field AND 6+ years of experience in cloud/infrastructure technologies, technology solutions, practice development, architecture, and/or consulting
- 8+ years of experience working in a customer-facing role (e.g., internal and/or external)
- 8+ years of experience working on technical projects
- Deep domain expertise in one of the Data-specific areas, such as Azure SQL Data (IaaS/PaaS), deployments and migrations to the cloud, Open-source database deployments and migrations, Cloud Scale Analytics, Data Governance, etc. OR hands-on experience working with the respective products at the expert level.
- Experience creating Data & Analytics Proof of Concepts (PoC), Minimum Viable Products (MVPs) for customers that lead to production deployments
- The technical aptitude and experience to learn new technologies and understand market and relevant cloud trends.
- Competitive Landscape: Knowledge of key Data & Analytics platforms such as AWS, GCP, Snowflake, etc.
- Partners: Understanding of partner ecosystems and the ability to leverage partner solutions to solve customer needs
- 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).