Soham J is a Senior Software Engineer in San Francisco with nine years of experience building production-grade systems that sit at the intersection of AI, data, and infrastructure. He moves quickly from ambiguous, high-leverage problems to pragmatic implementations, turning complex distributed and data-heavy logic into elegant, usable products. His background spans full-stack and backend work across Amazon (building an ML-powered AWS Entity Resolution service), Expedia, Cisco, and startups, demonstrating a consistent pattern of shipping scalable services and integrating ML into real products. Soham is an active contributor to Apache Drill, where he improved query-engine robustness and performance—work that reflects deep familiarity with memory management and distributed query semantics. Equally comfortable in low-level system debugging and product-facing web platforms, he combines systems thinking with a product-first mindset. He’s drawn to projects that don’t yet exist and enjoys building infrastructure that makes intelligence a repeatable product.
Apache Drill is a distributed MPP query layer for self describing data
Role in this project:
Back-end Developer
Contributions:23 commits, 187 PRs, 60 pushes in 1 year 4 months
Contributions summary:Soham primarily focused on improving the performance and addressing issues related to the Apache Drill query engine. Their contributions involved modifying the `LateralJoinBatch` implementation, specifically addressing memory management and vector allocation within the context of join operations. The commits also included resolving an IllegalStateException in `UnnestRecordBatch` and fixing a race condition in `RuntimeFilterSink`. Additionally, the user implemented support for the `EMIT` outcome in `ExternalSortBatch` and made enhancements related to the display of the query state in the query result page.
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