Courtney Holcomb
Engineering Manager, AI & Semantic Layer at dbt Labs
San Francisco, California, United States
Summary
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Rockstar🎓
Top SchoolCourtney Holcomb is an engineering manager specializing in AI and semantic layers with nine years of experience building data-first developer tooling from San Francisco. She rose from founding engineer roles to lead teams at dbt Labs after Transform's acquisition, combining hands-on backend work with people management. Courtney contributes to major open-source projects like dbt-core and MetricFlow, where she’s fixed parsing bugs, implemented semantic-layer filters, and enhanced Databricks integrations—work that directly improves metric and transformation correctness at scale. With a background that spans creative writing (UCLA) to software engineering (Hackbright), she brings strong communication and product sensibility to complex data engineering problems. Unusually, her path blends editorial leadership and recruiting experience with deep technical contributors’ instincts, making her adept at translating customer needs into robust engineering roadmaps.
9 years of coding experience
9 years of employment as a software developer
Software Engineering, Software Engineering at Hackbright AcademyUniversity of California, Los Angeles
English, Italian
Stackoverflow
1reputation
0reached
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Github Skills (10)
data-modeling10
databricks10
sql10
python10
data-engineering10
testing9
database-administration8
elt8
analytics8
business-intelligence7
Programming languages (4)
Github contributions (5)
dbt-labs/metricflow
Sep 2022 - Jan 2023
MetricFlow allows you to define, build, and maintain metrics in code.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:701 reviews, 148 commits, 711 PRs in 3 months
Contributions summary:Courtney primarily focused on enhancing the Databricks integration within the MetricFlow project. Their contributions included adding Databricks support, cleaning up and refactoring the Databricks client code, and enabling features like secondary connections for table renames. Additionally, they addressed errors related to query planning and implemented improvements to how the Databricks client handled data, including removing timezone information and optimizing data handling.
analyticsdatapypirecallbusiness-intelligence
dbt-labs/dbt-core
Mar 2023 - Dec 2024
dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications.
Role in this project:Back-end Developer
Back-end DeveloperContributions:23 reviews, 20 PRs, 72 pushes in 1 year 9 months
Contributions summary:Courtney primarily focused on fixing bugs and implementing new features related to filter parsing and data transformation within the dbt-core repository. Their contributions included modifying code in core files to improve data handling, along with adding tests. They also worked on enabling list filters and allowed metrics in semantic layer filters and custom granularities.
analyticsdbt-viewpointtransformanalystssql
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