I'm Vignesh Chandramohan — currently building DoorDash Data Platform, previously led engineering at Microsoft Azure Stream Analytics. I have built critical distributed systems and led high performing engineering teams. Passionate about stream processing, table formats, and the open-source communities building tomorrow's modern data stacks.
Enabling engineers, analysts and data scientists to build and manage analytical workflows — declarative batch and streaming ETLs, metric semantic layers, feature store ingestion, and marketing segmentation.
A SQL-based, managed stream processing service. Enables azure and Fabric customers to build near real-time analytics, and streaming ingestion to data lake. Mission critical internal and external streaming workloads run on the service.
An embedded key-value store leveraging object storage, built in Rust. A deeply technical community I learn from and care about.
Personal repositories spanning systems experimentation, stream processing prototypes, and tooling. A window into what I build when I'm learning something new.
A deep dive into SlateDB's architecture - object store primitives it relies on, and the properties it offers.
A short talk on how we use Apache Iceberg at DoorDash and the challenges we faced.
Available to speak on data platform architecture, stream processing, Iceberg, metrics and engineering leadership.Reach out →