Sandy Ryza
Member Of Technical Staff at Anthropic
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolSandy Ryza is a seasoned software engineer with 14 years of experience building data infrastructure and machine learning systems, currently a Member of Technical Staff in San Francisco. Former lead engineer on Dagster, Sandy helped design software-defined assets and advanced asset orchestration for production ML and data pipelines. An active open-source committer to Apache Spark and Hadoop, Sandy has contributed deep back-end work on YARN integration, schedulers, and large-scale time-series and NLP tooling. He co-wrote the O’Reilly book Advanced Analytics with Spark and maintains the companion aas code, reflecting a blend of practical ML modeling and systems engineering. Sandy moves fluidly between product-facing leadership and low-level distributed-systems problem solving—a pattern visible from running ML teams to fixing livelock bugs in Hadoop. He combines academic rigor (BS from Brown, cum laude) with a knack for turning research ideas into robust production software.
14 years of coding experience
13 years of employment as a software developer
Bachelor of Science (BS), Cum Laude and with Honors, Computer Science, Bachelor of Science (BS), Cum Laude and with Honors, Computer Science at Brown UniversityHigh School Diploma, High School Diploma at Crossroads School
Stackoverflow
275reputation
7kreached
12answers
1question
Github Skills (46)
hadoop-mapreduce10
apache-spark10
spark10
data-pipelines10
python10
back-end-development10
data-science10
decomposition10
data-engineering10
big-data10
machine-learning10
time-series10
distributed-systems10
mapreduce10
hadoop10
Programming languages (5)
Github contributions (5)
sryza/spark-timeseries
Feb 2015 - Jan 2017
A library for time series analysis on Apache Spark
Role in this project:
Data Scientist
Data ScientistContributions:361 commits, 97 PRs, 230 pushes in 1 year 11 months
Contributions summary:Sandy's contributions primarily focus on the development of a time series analysis library on Apache Spark. They implemented core functionalities related to time series data, including classes for representing and manipulating time series data, along with methods for calculating key metrics, such as autocorrelation. The user's work also extends to building ARIMA and GARCH models for time series forecasting.
time-series-analysisapachesparkscalaapache-spark
dagster-io/dagster
Jun 2020 - Jan 2023
An orchestration platform for the development, production, and observation of data assets.
Role in this project:Data Engineer
Data EngineerContributions:5 releases, 4161 reviews, 1085 commits in 2 years 7 months
Contributions summary:Sandy primarily contributed to enhancing the data engineering capabilities within the Dagster repository, with a focus on improving asset management. They implemented changes that introduced more flexibility, allowed for managing different partition definitions, and enabled more control over how assets are structured. Their contributions included modifying the GraphQL API to support various partition-related operations, enabling more precise control over asset materializations, and refining the core logic behind automated asset management.
operationpythonobservationschedulermetadata
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