Sharif
Doghmi

Sharif Doghmi has been working with large-scale data systems since 2012, and with Spark and Databricks since 2016. Throughout his career, he has architected, developed, and optimized many large-scale streaming and batch data pipelines, as well as machine learning pipelines, in both the advertising and finance industries.

Over the years, he has led numerous projects building cost-effective, reliable, and performant data processing apps, ML apps, and data platforms using best practices in data, software, and ML engineering. His approach emphasizes gaining a deep understanding of the pros and cons of different technologies and architectures, in order to select the most suitable tools and design strategies for the project at hand.