Building reliable ETL pipelines for MongoDB often means balancing speed, complexity, and governance. As data volumes grow and cases expand – from analytics to compliance – traditional approaches can quickly become brittle and time-consuming.

In this session, Siamion Makarski, Principal Engineer (Architecture), explores how AI-assisted techniques are reshaping MongoDB ETL design. Drawing on real-world scenarios, he will examine how natural-language-driven pipeline creation, automated transformations, and unified workflows can simplify common challenges such as data masking, aggregation for analytics, and event streaming with Kafka.

Attendees will gain practical insight into modern ETL patterns that reduce operational friction, shorten development cycles, and make MongoDB data pipelines easier to build, evolve, and govern.