Herman Van Hövell Tot Westerflier is a Senior Staff Software Engineer based in The Hague with 11 years of experience building and optimizing large-scale data systems. At Databricks he progressed from Senior Software Engineer to Senior Staff, driving performance and reliability work in Spark and Delta Lake. A longtime Apache Spark committer and PMC member, he focuses on backend data processing—particularly window function optimizations and thread-safe encoders—that improve SQL performance at scale. His open-source contributions also span low-level runtime and LLVM codegen work in Weld, showing comfort with compiler/runtime internals as well as distributed analytics. Combining a systems-engineering MSc from Delft with hands-on product and managing-director experience, he brings both technical depth and pragmatic ownership to complex data infrastructure.
11 years of coding experience
11 years of employment as a software developer
MSc, Business, Computer Science, MSc, Business, Computer Science at Delft University of Technology
Apache Spark - A unified analytics engine for large-scale data processing
Role in this project:
Data Engineer
Contributions:1489 reviews, 13 commits, 575 PRs in 6 years 3 months
Contributions summary:Herman's commits primarily focus on improvements and optimizations related to Spark's data processing capabilities, particularly in the area of window functions. The contributions include performance enhancements and code cleanups related to window function implementations in SQL. The commits involve modifications to the core of Spark SQL, including the Window operator, indicating a focus on backend data processing and optimization. They also show contributions to tests of Window functions.
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:40 reviews, 6 commits, 2 PRs in 1 year 2 months
Contributions summary:Herman primarily contributed to the Delta Lake project by implementing and refining core functionalities within the Spark ecosystem. Their commits focused on optimizing performance, such as preventing unnecessary jobs in specific scenarios, and enhancing the thread safety of ExpressionEncoder usage. The user also addressed various bugs and re-enabled tests, demonstrating a focus on the stability and reliability of the Delta Lake library. Furthermore, the user refactored code related to invariant checks, indicating a commitment to maintainability and code quality.
analyticsprestodbflinkbig-dataspark
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