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, LLMOps, 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