Thomas Lento
Staff Software Engineer at Binti
Menlo Park, California, United States
Summary
🤩
Rockstar🎓
Top SchoolThomas Lento is a Staff Software Engineer based in Menlo Park with a multidisciplinary background spanning sociology, data science, hands-on engineering, and management. He architected and integrated MetricFlow into dbt Labs’ cloud product to power a semantic metric layer, and previously led its design and roadmap while at Transform, contributing significant back-end and data-engineering work to the open-source MetricFlow project. Thomas brings production-scale privacy and logging expertise from a decade at Facebook, including building automated deletion systems and driving cross-team privacy alignment. He combines academic rigor (PhD in Sociology) with pragmatic system design, often translating customer-facing product needs into robust data and parsing implementations. An uncommon trait: he moves fluidly between research, product-facing metric logic, and low-level parsing/refactoring work, enabling both strategic direction and detailed code contributions.
4 years of coding experience
19 years of employment as a software developer
BA, Chemistry, Asian Studies, BA, Chemistry, Asian Studies at Cornell University
Japanese, English
Github Skills (12)
pydantic10
python10
yaml10
testing9
data-engineering9
data-modeling9
data-pipeline7
data-pipelines7
databricks6
snowflake5
postgresql5
bigquery5
Programming languages (4)
Github contributions (5)
dbt-labs/metricflow
Apr 2022 - Jan 2023
MetricFlow allows you to define, build, and maintain metrics in code.
Role in this project:
Back-end Developer & Data Engineer
Back-end Developer & Data EngineerContributions:13 releases, 1116 reviews, 228 commits in 9 months
Contributions summary:Thomas primarily worked on improving the `MetricFlow` project, focusing on the internal model definition and parsing of model files. They implemented fixes for parsing and handling of different input types, particularly string types and metric definitions. Key contributions include refactoring the model to use more robust Pydantic parsing, improving support for None types in data warehouse implementations, and adding tests for data source, metric, and materialization configuration parsing.
analyticsdatapypirecallbusiness-intelligence
tlento/test_public
May 2022 - May 2022
A public repo for testing stuff out.
Contributions:10 PRs, 7 pushes, 8 branches in 1 day
testingpublic-repo
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