He leads the Analytics & AI teams and oversees initiatives related to analytics platforms, data valorization, and the deployment of artificial intelligence solutions. His work focuses in particular on data democratization, AI agents, and the integration of AI into business and decision-making processes within a highly regulated environment.

Migrating an on-premises data platform to GCP is much more than just a technical project. It involves a series of critical decisions, often made under pressure: lift and shift, or rewrite from scratch? How do you keep dashboards up and running during the transition? How do you manage two platforms side by side without burning out? Which GCP components should you invest in? And above all—how do you prevent the cloud bill from spiraling out of control?
Hatem will share the choices made, the mistakes avoided, and the trade-offs that make the difference between a successful migration and a project that gets bogged down.

He oversees a team responsible for data governance and data quality and drives the structuring of enterprise data processes. His work focuses on strengthening data reliability and consistency, enabling data usage that is both compliant and value‑driven, and enhancing the operational effectiveness of the Data Analytics department.

Nicolas Szewe leads enterprise AI and data transformations, with a focus on turning ambition into measurable business outcomes.
He specializes in moving from strategy to execution, building scalable AI platforms, defining pragmatic roadmaps, and embedding data-driven decision-making at scale. In regulated environments, he prioritizes governance, reliability, and relevance over hype.
He has built AI and BI functions from scratch, delivering high-impact use cases while developing teams grounded in ownership and continuous learning. He works closely with senior leadership to focus investments where they materially improve performance and competitiveness.

Benoit leads the evolution of FHVi’s enterprise data platform and drives initiatives around modern data architecture, interoperability, governance, and analytics services for healthcare institutions across the canton of Vaud. During this roundtable, he will share practical insights on transitioning from traditional Datawarehouse approaches toward a modern Lakehouse architecture, balancing scalability, security, interoperability, and business value in a highly regulated environment.

Juan Daniel Moreno is a senior Data executive with more than 14 years of experience leading data transformation initiatives within international financial institutions and highly regulated environments. As Head of Data in a Geneva-based private bank, he specializes in Data Governance, Data Products, Data Mesh, and Data Quality, helping organizations turn data into strategic business assets.
He combines strong strategic vision with hands-on execution capabilities across the full data lifecycle. His expertise enables organizations to strengthen data reliability, regulatory compliance, risk management, and decision-making through modern and scalable data operating models.
Juan Daniel also serves as President of DAMA Geneva, where he actively contributes to the advancement of the Data Management community and promotes industry best practices across Switzerland’s French-speaking region.

Building scalable ingestion pipelines for a global insurer that operates around the clock is a constant balancing act — cost efficiency vs. flexibility, speed vs. governance, local autonomy vs. enterprise cohesion. When data never stops flowing across time zones, every architectural decision has a direct impact on both the bottom line and the ability to move fast.
This is exactly where Arnaud operates by leading a team of Data Solution Architects and a Lead Data Modeler, which designs data solutions from ingestion through to consumption. He will share how Zurich tackles cost optimization at global scale and leverages GenAI to accelerate pipeline development.

While data is widely recognized as the driving force behind modern healthcare strategies, it can be both an invaluable clinical asset and a latent liability if not governed properly. Because taking care of sensitive health information requires significant time, resources, and trust, Vincent Rejany works at the crossroads of clinical care, medical research, IT, and administration at the Geneva University Hospitals (HUG). As Head of Data Platform, he gathers and prioritizes healthcare data requirements to define the overarching vision for the clinical data platform.
To make data management smarter and less cumbersome, he leverages 10 years of experience in Product Management specializing in Data and Artificial Intelligence.
His team focuses on critical data management domains, including healthcare system interoperability, secure data integration, and clinical data quality and governance.

Mathieu Fivaz leads the development of agentic AI systems for cybersecurity operations, designing autonomous agents that assist analysts and automate investigations across complex security environments. His work focuses on using ontologies and graph-structured data to connect identities, assets, alerts, behaviors, and infrastructure, enabling AI systems to surface the most relevant information and support reliable, high-quality cybersecurity investigations.

Charlotte led the first AI initiatives at TL, where the main challenge was less about the models themselves and more about everything around them: governance, collaboration with IT, data access, and tool selection. Her work helped shape TL’s shift toward a more pragmatic and scalable approach to AI, focused on business needs and model explainability in operational decision-making.

Arnaud Gaillard is a technology professiona at Nagra Kudelski, where he serves as Principal Architect and Data Services Team Leader. He brings his expertise in data architecture and strategy to ensure the efficient development and deployment of the company's data virtualization/exposition and AI integration platform.

Benoît's is responsible for the Givaudan's Platform Engineering capabilities, leading teams across Data Streaming & Integration and DevSecOps technologies.
His role focuses on aligning technology platforms with IT Product Lines priorities, enabling product teams with secure, scalable, and easy-to-use integration and software engineering capabilities.
He drives the adoption of modern engineering practices and technology foundations that enhance developer productivity, accelerate delivery, and support innovation.

Guillaume Hayoz has successfully implemented data governance at Swissquote by taking a pragmatic, step by step approach focused on demonstrating tangible business value. He has led the integration of data quality and governance practices across the organization by addressing one of the key challenges of any data governance initiative: engaging employees in new responsibilities that often fall outside their formal job descriptions. Through gradual adoption, clear value creation, and strong organizational alignment, he has helped embed data governance as a sustainable business practice within Swissquote.

He began his career as head of data at Losinger Marazzi, a Bouygues Construction subsidiary in Switzerland, before joining Bouygues Bâtiment International 3 years ago. With nearly 10 years of experience in data management, he coordinates data strategies and initiatives across a dozen countries.
He leads an international data community and promotes data and AI adoption globally. By fostering collaboration on a shared data infrastructure, it transforms data into a reliable, accessible asset that enhances decision-making and operational performance.
His current challenges include deploying Agentic AI, scaling Data Products and Data Mesh approaches, and implementing associated governance frameworks.