Hussein Awala is a Senior Data Engineer based in Paris with 8 years of experience building scalable data platforms and pipelines across ads, classifieds, and risk analytics. He combines hands-on production engineering at Datadog and Voodoo with open-source stewardship as an Apache Airflow committer and PMC member, contributing core scheduler and dataset-metrics improvements to one of the most widely used workflow engines. Comfortable across PySpark, Airflow, Argo, Kubernetes and cloud storage, he focuses on reliability, observability and automation to bring ML models and streaming systems into production. At leboncoin and Data4Risk he led platform optimizations, security and GDPR-aware data architectures while mentoring cross-functional teams. Notably, his Airflow work includes nuanced improvements to sensors, CLI task dependency handling and data interval semantics that reduce operational complexity at scale. He blends academic training in data science with pragmatic product-facing delivery, favoring measurable impact over novelty.
8 years of coding experience
5 years of employment as a software developer
Master's degree Computer Science, Master's degree Computer Science at Lebanese University - Faculty of Sciences
Master's degree Data Science, Master's degree Data Science at National School of Computer Science and Applied Mathematics of Grenoble
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Role in this project:
Back-end Developer & Data Engineer
Contributions:2404 reviews, 769 PRs, 358 pushes in 2 years 10 months
Contributions summary:Hussein primarily focused on enhancements to the core functionality of the Apache Airflow platform. Their work involved adding features like a maximum wait interval for exponential backoff in the BaseSensor and implementing improvements for handling past dependencies in the Airflow CLI tasks. The user also contributed to the addition of statsd metrics for datasets, and they made modifications to data interval handling, demonstrating their involvement in data engineering aspects of the project.
A Python package to submit and manage Apache Spark applications on Kubernetes.
Contributions:18 releases, 1 review, 230 PRs in 1 year 1 month
airflowkubernetespythonspark
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