Data Engineering, AI Experimentation, Health Tech, and Data Platforms are reshaping enterprise innovation. In this episode of Builders, Jonas Dieckmann, Global Manager of Data Intelligence & Team Lead of Data Engineering at Philips, explains how one of the world’s largest health tech companies is scaling AI through cross-functional collaboration, domain-driven data platforms, and rapid experimentation. Why do so many enterprise AI initiatives fail — and what is Philips doing differently?
Jonas shares:

• How AI squads accelerate innovation inside large organizations
• Why short AI experiments lead to faster business impact
• The evolution from centralized platforms to data mesh architectures
• How metadata and data lineage are becoming critical for AI success
• The biggest challenges in healthcare data and governance
• What makes a great data engineer in the AI era
• The trends shaping the future of data and AI

If you’re building data platforms, scaling AI teams, or navigating enterprise transformation, this episode delivers practical insights from the frontlines of global health tech.
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#DataEngineering #AI #HealthTech #DataPlatform #DataMesh #Philips
Chapters
(00:00) How Philips Is Driving Data Innovation in Health Tech
(01:24) Jonas Dieckmann’s Journey Into Data & AI Leadership
(02:44) The Biggest Challenges of Data Platforms in Healthcare
(05:27) Why Health Tech Data Is More Complex Than Most Industries
(08:07) Inside Philips’ AI Squad Strategy for Innovation
(13:15) How Philips Chooses AI Use Cases That Actually Matter
(16:36) Why Fast AI Experiments Lead to Better Results
(22:46) The Shift From Centralized Data Platforms to Data Mesh
(28:35) Data Governance and Ownership in a Data Mesh World
(30:37) What Future Data Platforms Must Support for AI
(33:01) Why Metadata and Data Lineage Are Becoming Essential
(35:26) What Separates Great Data Engineers From the Rest
(39:58) How Philips Evaluates Talent for Data & AI Teams
(45:30) The Most Exciting Trends in Data and AI Right Now
(47:39) The Biggest Mistakes Companies Make When Scaling AI
(50:03) Jonas Dieckmann’s Vision for the Future of Data at Philips