Christophe Duong is a Lead Data & Analytics Engineer with 11 years of experience building and scaling end-to-end data platforms and machine learning systems across startups and enterprise settings. He combines deep technical chops—from designing ingestion and orchestration (Dagster, dbt) to deploying large-scale recommender systems and NLP pipelines on cloud platforms—with hands-on leadership in hiring and growing data squads. Christophe has repeatedly taken projects from zero to production (Airbyte, Comet, DinMo) and specializes in making data usable for diverse stakeholders through analytics engineering, semantic layers, and observability. Comfortable as a freelance operator, he accelerates data maturity and product-led insights for fast-moving companies while teaching teams to raise their data literacy. A former research engineer in medical imaging and early DARPA-funded work, he brings uncommon experience translating advanced ML prototypes into reliable, business-focused production systems.
11 years of coding experience
10 years of employment as a software developer
Online Course Mining Massive Datasets, Online Course Mining Massive Datasets at Stanford University through Coursera
Master's degree major in Cognitive Sciences and Artificial Intelligence Computer Science, Master's degree major in Cognitive Sciences and Artificial Intelligence Computer Science at EPITA: Ecole d'Ingénieurs en Informatique
MOOC (the first or among the pioneer that were really massive ones) Introduction to Artificial Intelligence, MOOC (the first or among the pioneer that were really massive ones) Introduction to Artificial Intelligence at Udacity
Master's Degree Business Analytics & Big Data, Master's Degree Business Analytics & Big Data at IE Business School
Airbyte is an open-source data integration engine that helps you consolidate your data in your warehouses.
Contributions:4 PRs, 9 pushes, 65 branches in 3 months
data-sourcedatawarehousedatadata-ingestionsql
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