Meng Tong is a software engineer and co-founder based in San Francisco with 5 years of professional experience building data infrastructure, observability, and lakehouse systems. He has delivered core backend improvements at Databricks and contributed to the widely-used open-source Delta Lake project—refactoring SQL configs, adding operational metrics for DELETE/TRUNCATE/UPDATE, and fixing merge and log-store bugs. Prior roles span Observe and ZettaBlock focused on streaming and data infra, and earlier years at AWS on Amazon Redshift query processing, giving him deep experience across storage, query engines, and production telemetry. Now leading a stealth startup, he pairs hands-on systems engineering with product instincts and a track record of making complex data platforms more maintainable and measurable.
An open-source storage framework that enables building a Lakehouse architecture with compute engines including Spark, PrestoDB, Flink, Trino, and Hive and APIs
Role in this project:
Back-end Developer
Contributions:4 reviews, 34 commits, 5 PRs in 1 year
Contributions summary:The user, Meng Tong, primarily contributed to enhancing the Delta Lake storage framework. Their work focused on refactoring and adding metrics for commands such as DELETE, TRUNCATE, and UPDATE. The user also refactored configurations and SQL conf entries, improving the overall maintainability of the project. Furthermore, they addressed bugs related to log store functionality and generated column support within the merge command.
An open-source storage layer that brings scalable, ACID transactions to Apache Spark™ and big data workloads.
Contributions:1 branch in 1 day
scalableworkloadssqlapachebig-data
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