Many Data Engineers play very reactive roles. Because of that they struggle with cross-org collaboration, getting a seat at the table, creating alignment, and making their data producers produce high-quality data for them.

But there's another way – Data Engineers can LEAD!

Data Engineers sit at the intersection of data and their business, and if they execute well, they can play a very pivotal role!

In this talk, Orr and Shachar will explain what it looks like when you lead as a Data Engineer, and give practical suggestions for ways to apply that in your job.

Many Data Engineers play very reactive roles. Because of that they struggle with cross-org collaboration, getting a seat at the table, creating alignment, and making their data producers produce high-quality data for them.

But there's another way – Data Engineers can LEAD!

Data Engineers sit at the intersection of data and their business, and if they execute well, they can play a very pivotal role!

In this talk, Orr and Shachar will explain what it looks like when you lead as a Data Engineer, and give practical suggestions for ways to apply that in your job.

Practicing analytics well takes more than just tools and tech. It requires data modeling practices that unify and empower all teams within analytics, from engineers to analysts. This is especially true as AI becomes a part of analytics. Without a governed data model that provides consistent data interpretation, AI tools are left to guess. Join panelists Joe Reis, Sarah Levy, Harry Gollop, Rob Hulme, Shachar Meir, and Guy Fighel, as they share battle-tested advice on overcoming conflicting definitions and accurately mapping business intent to data, reports and dashboards at scale. This panel is for data & analytics engineers seeking a clear framework to capture business logic across layers, and for data leaders focused on building a reliable foundation for Gen AI.