Tech lead for stream processing runtime.

Improvements to Observe's stream processing pipeline to support new ingestion modes, reduce latency, and improve reliability. More work to support tracing capabilities in the platform. GeoIP lookup. S3 export. Mentored interns and new hires.

OPAL query language + compiler. Query execution and optimization. Foundational work to support tracing capabilities. Incremental view maintenance.

Built an end-to-end tool to profile heap memory usage from third-party libraries in the Azure Sphere operating system, to help customers make their applications more memory efficient.

Wrote proxies for C standard library memory functions to efficiently record heap allocation statistics on the Azure Sphere IoT device and expose them through HTTPS to the user on a connected PC.

Retrieved these statistics from devices and visualized them on the user end using Python.

Implemented a process to verify and correct usage metadata ("metering data") in an object storage system.

Created new metering data structures using Google Protocol Buffers, and updated the metering aggregation process using concurrent Java code.

Implemented a process to automatically correct metering data by parsing a log of storage operations.

Reduced metering service downtime through data structure design, which aligned with log structure such that the new correction process could run without pausing the metering service.