Modern distributed systems generate massive volumes of telemetry data requiring fast query processing for real-time monitoring and analytics. As data volumes reach petabyte scale, traditional query architectures struggle to balance execution flexibility, resource utilization, modularity, cost efficiency, and performance. This thesis addresses these challenges through the design and implementation of Bolt, a query engine for large-scale event processing systems. The research demonstrates how to extend existing production infrastructure without disrupting operational stability, using a composable approach and standardized interfaces while maintaining compatibility with established distributed architectures. Chapter 1 establishes the problem statement: extending query capabilities for high-demand analytical workloads while addressing challenges in execution flexibility, resource utilization, modularity, and cost efficiency.