Scott Brenstuhl is a Senior Data Platforms Engineer in the San Francisco Bay Area with 11 years of experience turning disparate operational systems into reliable, analytics-ready platforms. He’s built data warehouses, CI/CD for dbt, serverless ingestion pipelines, and orchestration with Step Functions, and was the first data hire at Extend where he transformed DynamoDB and multiple third-party sources into tidy columnar data. Scott pairs hands-on engineering (Python, R, AWS, dbt) with product-minded data enablement—mentoring analysts, documenting dev environments, and automating workflows that save teams hours daily. His background in operations and Salesforce automation gives him a rare cross-functional lens for shipping data solutions that align with business processes. An active contributor to the ropensci/skimr project, he’s improved type handling in R summary tooling, reflecting both practical production chops and attention to data nuance.
11 years of coding experience
11 years of employment as a software developer
Bachelors, Finance, Bachelors, Finance at Miami University
A frictionless, pipeable approach to dealing with summary statistics
Role in this project:
Back-end Developer
Contributions:6 commits, 2 PRs, 2 comments in 1 day
Contributions summary:Scott contributed to the `skimr` R package by adding and modifying functionality to handle different data types within the summary statistics framework. Specifically, they implemented support for the `hms` and `difftime` data types, creating and adjusting functions to correctly process and display their statistics. The user also addressed and resolved merge conflicts, demonstrating experience in version control and collaborative development within the project. Their work primarily involved modifying core functions and tests to ensure accurate data type handling.
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