The data engineer’s role is shifting in the AI era. With LLMs and agents as new consumers, the challenge moves from SQL and schemas to semantics, context engineering, and making databases LLM-friendly. This session explores how data engineers can design semantic layers, document relationships, and expose data through MCPs and AI interfaces. We’ll highlight new skills required, illustrate pipelines that combine offline and online LLM processing, and show how data can serve business users, developers, and AI agents alike.
talk-data.com
L
Speaker
Lee Twito
1
talks
Generative AI Lead
Lemonade
Lee is Generative AI Lead and Co-Host of LangTalks. He has led multiple teams in building AI agents, including automating over 50% of customer support tickets, advanced document analysis pipelines, a voice agent, advanced tools for controlling agents in production, and an AI-coding platform and practices deployed across the R&D organization. Alongside his leadership work, Lee has hands-on experience building a wide range of AI agents, including sophisticated software engineering agents.
Bio from: Big Data LDN 2025
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