Enterprise Data & AI Platform Architect (f/m/x)

We are looking for an experienced Enterprise Data & AI Platform Architect to join a large-scale transformation program within the healthcare sector. In this strategic leadership role, you will be responsible for defining and evolving the technology foundation that supports enterprise-wide data, analytics, automation, and artificial intelligence initiatives. Working in a complex and highly regulated environment, you will drive the design of scalable platform capabilities while leading cross-functional teams and ensuring alignment between business objectives and technology strategy.

Your tasks

• Defining and executing the long-term architecture strategy and roadmap for data and AI platforms
• Leading platform governance, technology selection processes, and strategic decision-making related to enterprise solutions
• Enabling advanced analytics and AI adoption through scalable, reusable, and secure platform capabilities
• Driving platform reliability, operational excellence, automation, and service delivery across global environments
• Establishing cost management frameworks, budgeting practices, and optimization initiatives for cloud-based services
• Building and leading international teams responsible for platform architecture, engineering, operations, and continuous improvement
• Requirements
• Minimum 10 years of experience in data platforms, data engineering, or enterprise data architecture, including at least 5 years in an Architect role leading technical teams and large-scale platform initiatives
• Strong hands-on expertise with Databricks, Azure Data Services, and enterprise-scale Lakehouse architectures, including the design of scalable and governed data platforms
• Proven experience designing and operating cloud-native solutions across Microsoft Azure and AWS, including Infrastructure as Code, automation frameworks, CI/CD practices, and multi-region deployments
• Experience delivering AI and Generative AI platforms, including MLOps, LLM
• Ops, semantic layers, AI-driven analytics, conversational BI, RAG architectures, vector search, model serving, and intelligent agent-based solutions
• Strong knowledge of cloud FinOps, platform governance, cost optimization strategies, capacity planning, showback/chargeback models, workload management, and operational automation
• Previous work with enterprise data ecosystems, including Data Governance, Data Cataloging, Master Data Management (MDM), enterprise integration platforms, RPA solutions, and compliance requirements within regulated environments
• Excellent stakeholder management and communication skills, with fluent spoken and written English