In this episode of the Data Engineering Show, host Benjamin Wagner sits down with Xavier Gumara Rigol, Head of Data at Manychat, to discuss how artificial intelligence is fundamentally transforming data roles, organizational structures, and the future of analytics platforms while creating new types of work rather than eliminating existing ones.

- How to transition data analyst work from query delivery to AI-powered self-service analytics —  moving from Tableau dashboards to natural language-to-SQL-to-insight tools that let business users answer their own questions with high accuracy

- Why cross-functional team structures beat siloed data organizations — embed data analysts and scientists directly within product teams focused on specific business problems rather than centralizing them in separate departments

- The "Build vs. Buy" framework for AI analytics tools in 2026 — evaluate text-to-SQL solutions based on BI tool consolidation, programmatic manageability, cost competitiveness, and your organization's readiness for AI integration

- How to structure data platform teams to enable autonomous work — create a central platform team that manages infrastructure, data quality, privacy, and compliance so embedded analysts can operate independently

- The critical role of context layers for LLM accuracy — well-structured metadata and context on top of your data warehouse is essential for achieving high-accuracy natural language queries at scale

- Why greenfield projects move faster with AI than legacy platforms — newly built systems with AI require less headcount than legacy systems, but maintaining existing data infrastructure still demands human expertise for years to come

Xavier is the Head of Data at Manychat, leading the Machine Learning and Data Platform team with over a decade of experience in the data ecosystem. With a background spanning BI development to data platform management, he has become a thought leader on bridging the divide between data and product functions—a topic he explored in depth through his published book. In this episode, Xavier shares transformative insights on how AI is reshaping data team structures, roles, and workflows, providing actionable strategies for organizations looking to build more versatile, cross-functional data teams. His work implementing natural language-to-SQL analytics agents and customer-facing analytics platforms demonstrates the practical impact of AI adoption in modern data platforms, making this conversation essential for data leaders navigating the rapidly evolving landscape of AI-driven analytics.

"I think that the most exciting thing that we are working on at the moment is this natural language to SQL to insight type of tool." - Xavier Gumara Rigol

"The type of work is changing. It's not going anywhere, but it's changing." - Xavier Gumara Rigol

"Data roles that are value creators, like data analysts and data scientists, need to work in a cross-functional team with a product manager and with a specific problem to solve." - Xavier Gumara Rigol

"We are repurposing things to do more things at the same time. And this is the benefit of AI and how we are taking advantage today." - Xavier Gumara Rigol

"To provide high accuracy in the answers, you need to have a very well-structured and built context layer on top of your data warehouse." - Xavier Gumara Rigol

"The barrier to building has been lowered quite a lot, and we could provide something very quick, very fast to the rest of the organization." - Xavier Gumara Rigol

"For the current platforms to be maintained and for the current capabilities to be maintained, you will still need humans for quite a few years." - Xavier Gumara Rigol

"Everything that you create in the system should be able to be created in text because we want to work with this with LLMs and generative AI." - Xavier Gumara Rigol

"If you start from scratch, you probably can get to a nice place where you need fewer people to maintain in comparison to if you were to build this three years ago." - Xavier Gumara Rigol

"We still need a data analyst in the company, and we will need them for a long time." - Xavier Gumara Rigol

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