Summary
Hamza Mogni is a Data Engineer with 9 years of hands-on software and data engineering experience, currently building scalable data platforms and ML-enabled systems. He specializes in Python, Airflow, Elasticsearch, Celery/RabbitMQ, and cloud-native deployments (Azure AKS, Data Lake, Terraform, GitHub Actions), and has a strong DevOps mindset around CI/CD and IaC. At Deepecho he accelerated on-device inference by 800% for ultrasound video processing using Raspberry Pi, ArmNN and optimized ML runtimes, and designed end-to-end data and inferencing pipelines. He has repeatedly built distributed ingestion and search systems—designing OLTP schemas, Airflow pipelines, and Elasticsearch analytics—for startups and products he co-founded. Based in Morocco, he pairs product-focused engineering with low-level optimization experience, regularly moving prototypes from edge devices into production cloud infrastructure.
9 years of coding experience
4 years of employment as a software developer
Diplôme d'Ingénieur d'état, Géoinformation / SIG, En cours (2ème année du cycle d'ingénieur), Diplôme d'Ingénieur d'état, Géoinformation / SIG, En cours (2ème année du cycle d'ingénieur) at Faculty of Science and Technology Tangier
Diplome Universitaire de Technologie, Computer Science, Diplome Universitaire de Technologie, Computer Science at Université Ibn Zohr
English, French, Arabic