Umer is a Staff Data Engineer at Chime, where he builds data foundations, experimentation platforms, and internal engineering frameworks in highly regulated fintech environments. He previously worked at Meta on large-scale batch and streaming systems supporting core product analytics.

His work focuses on creating frameworks that abstract complex data transformations and standardize semantics, enabling reliable experimentation and analytics across teams. Recently, he has been leading efforts to automate semantic model creation for data warehouse tables and build a centralized semantic repository that serves as trusted context for AI agents.

He is particularly interested in the intersection of data modeling, analytics engineering, and applied AI in production systems.