Chaerin Lee
Senior Consultant at Avanade
Denver Metropolitan Area United States
Summary
👤
Senior🎓
Top SchoolChaerin Lee is a Senior Consultant and data engineering specialist with six years of experience helping organizations build modern, analytics-driven pipelines and BI solutions. She blends machine learning, data engineering, and reporting expertise—having advanced through roles at Avanade from Analytics Engineer to Senior Consultant—while holding a Master’s in Business Analytics and a BS in Biochemistry. Chaerin contributes to prominent open-source dbt projects, notably refactoring dbt-utils to add cross-database dispatching and improve macro reusability, demonstrating a focus on maintainable, portable analytics code. Comfortable optimizing SQL for accuracy and performance, she pairs technical rigor with a research background in lab workflows and a knack for translating messy data into actionable insights. Outside work she’s an avid Denver food explorer and Rocky Mountain snowboarder, a detail that hints at her curiosity and love for practical experimentation.
6 years of coding experience
2 years of employment as a software developer
Master's degree, Business Analytics, Master's degree, Business Analytics at University of Colorado Boulder
Github Skills (13)
macros10
data-modeling10
sql10
dbt10
data-warehouse10
datamart10
refactor9
refactoring9
postgresql8
relational-databases7
sql-database7
database7
databases7
Programming languages (7)
Github contributions (5)
dbt-labs/jaffle-shop-classic
Jul 2021 - Sep 2021
A self-contained dbt project for testing purposes
Role in this project:
Database Engineer / Database Administrator
Database Engineer / Database AdministratorContributions:14 commits, 1 PR in 2 months
Contributions summary:Chaerin primarily focused on modifying SQL queries within the `models/customers.sql` and `models/orders.sql` files. These changes involve updating `JOIN` conditions, adjusting `GROUP BY` clauses, and altering the structure of calculated fields, suggesting a focus on optimizing data retrieval and aggregation within the dbt project. The commits demonstrate an understanding of relational database concepts, specifically focusing on refining how data is joined and aggregated in the data transformation process. This work likely contributed to improving data accuracy or query performance within the analytical models.
self-containeddbt-packagestestingsqlbigquery
dbt-labs/dbt-utils
Jan 2021 - Jan 2021
Utility functions for dbt projects.
Role in this project:Back-end Developer / Data Engineer
Back-end Developer / Data EngineerContributions:1 review, 8 commits, 1 comment in 1 day
Contributions summary:Chaerin primarily focused on generalizing and refactoring dbt-utils macros, making them adaptable across different data platforms. The commits involved modifying macros related to logging, date/time manipulations, pivoting, unpivoting, and generating series, improving their flexibility and reusability. A key contribution was the introduction of a dispatch mechanism, allowing the macros to adapt to different database dialects. These changes improved the project's maintainability and cross-database compatibility.
dbtutility-functionssqlterminology
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