Data Solutions Architect
时间：8月~12月2026年，可扩展能力：0.5 FTE 远程，需要在布拉格获得欧盟公民身份的笔记本电脑收集。角色重点是设计和改进基于 Azure 和 Databricks 的主要 AI 和数据应用程序使用案例。建筑师将与配送团队，平台团队，安全和业务利益相关者合作，将用案要求转化为实用的可重复使用解决方案设计。责任 ·设计解决方案架构用于人工智能，数据和 API 基础上的应用程序。·审查现有使用情况架构并建议更多可重复利用，高效和可维护的设计。· 通过帮助团队采用共享模式，平台功能和可重复使用组件来支持人工智能现代化。·定义应用程序，数据，Azure 服务，内部平台和第三方解决方案之间的集成模式。· 为实施团队准备架构文档，安全评估输入和设计材料。· 在交付团队，平台团队，安全和其他利益相关者之间协调建筑主题。技术背景 · Databricks 平台功能包括 Apps,Lakeebase,Genie 以及相关的 AI/数据服务。· 亚洲平台服务，包括 API 管理，身份控制和访问控制，数据库，消息传递和基于 Kubernetes 的应用程序托管。· AI/数据使用案例如文件处理，OCR,分类，信息提取，LLMOps,API 集成和工作流动自动化。个人资料 ·对企业应用设计的良好理解。· Azure 基础的企业解决方案的经验。· 数据 bricks,AI,分析和应用程序使用案例的经验.. ·了解 API,系统集成，身份，访问管理和安全应用程序设计。·与技术和非技术利益相关者合作的能力。· 能够清楚地记录建筑决策并指导实施团队。最初发布在喜马拉雅地区
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This is a remote position.
Period:August–December 2026, with possible extension
Capacity: 0.5 FTE
Remote, with laptop collection in Prague
EU citizenship required
About the role
The role is focused on designing and improving AI and data application use cases built mainly on Azure and Databricks. The architect will work with delivery teams, platform teams, security, and business stakeholders to translate use case requirements into practical reusable solution designs.
Responsibilities
- Design solution architecture for AI, data, and API-based applications.
- Review existing use case architectures and propose more reusable, efficient, and maintainable designs where needed.
- Support AI modernization by helping teams adopt shared patterns, platform capabilities, and reusable components.
- Define integration patterns between applications, Databricks, Azure services, internal platforms, and third-party solutions.
- Prepare architecture documentation, security assessment inputs, and design materials for implementation teams.
- Coordinate architecture topics across delivery teams, platform teams, security, and other stakeholders.
Technology context
- Databricks platform capabilities including Apps, Lakebase, Genie, and related AI/data services.
- Azure platform services, including API Management, identity and access control, databases, messaging and Kubernetes-based application hosting.
- AI/data use cases such as document processing, OCR, classification, information extraction, LLMOps, API integrations, and workflow automation.
Profile
- Good understanding of enterprise application design.
- Experience with Azure-based enterprise solutions.
- Experience with Databricks in data, AI, analytics, and application use cases.
- Understanding of APIs, system integration, identity, access management, and secure application design.
- Ability to work with both technical and non-technical stakeholders.
- Ability to document architecture decisions clearly and guide implementation teams.
Originally posted on Himalayas