Raphael Taylor-davies
Chief Technology Officer at Opfyx
United Kingdom
Summary
🤩
Rockstar🎓
Top SchoolRaphael Taylor-davies is a Chief Technology Officer and software engineer with 11 years’ experience building cloud-native and embedded systems, grounded in a Computer Science degree from Cambridge. He is proficient in C/C++, Rust, Python and Go and comfortable across the stack—from low-level firmware and vehicle networking to Kubernetes-managed services and hybrid cloud infrastructure. Raphael has driven platform and observability work at companies like InfluxData and Depop and led hybrid cloud, GPU and data-platform efforts at an autonomous vehicle startup. An active contributor to major Apache projects (arrow, arrow-rs, datafusion) and the Vector observability pipeline, he focuses on performance optimizations, null-handling correctness and efficient data handling for high-throughput systems. Colleagues rely on him for pragmatic architecture that bridges ML, streaming data and production reliability, and he’s known for digging into implementation details that others often miss.
11 years of coding experience
4 years of employment as a software developer
St Paul's SchoolBachelor's degree Computer Science, Bachelor's degree Computer Science at University of Cambridge
Github Skills (45)
kubernetes10
observability10
protocol-buffers10
query-optimization10
object-storage10
data-structure10
apache-arrow10
prometheus10
go10
aws10
performance-optimization10
kubernetes-pods10
parquet10
data-structures10
rust10
Programming languages (18)
Github contributions (5)
apache/arrow-rs
Dec 2021 - Jan 2023
Official Rust implementation of Apache Arrow
Role in this project:
Back-end Developer
Back-end DeveloperContributions:4663 reviews, 421 commits, 2857 PRs in 1 year 1 month
Contributions summary:Raphael primarily focused on enhancing the performance of the object store through the addition of specialized optimizations and features. They improved the efficiency of various functionalities, especially related to byte array handling and dictionary-encoded data, leading to performance gains. The user introduced functionalities that allow control over the formatting of values and improvements in handling null values, improving the overall code quality and performance. Furthermore, they added support for handling object versions during put operations, enhancing overall data management.
rustolapapachearrowapache-arrow
apache/datafusion
Feb 2022 - Jan 2023
Apache DataFusion SQL Query Engine
Role in this project:Back-end Developer
Back-end DeveloperContributions:955 reviews, 97 commits, 419 PRs in 11 months
Contributions summary:Raphael primarily contributed to the development of the datafusion SQL query engine. Their contributions focused on enhancing the engine's capabilities and functionality, specifically related to supporting grouping, sorting, and merging operations. This included the addition of features like sort-preserving merge, allowing for optimized operations on pre-sorted partitions, and improvements to how boolean expressions are converted. They also worked on optimizations related to the handling of null values and ensuring the engine's performance.
querypythonquery-enginedataframerust
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