Description

Data Engineer specializing in building scalable cloud data pipelines and modern data architectures.

I design end-to-end data solutions using Snowflake, Apache Airflow, Python, and SQL—transforming billions of records into actionable insights for analytics and AI applications.

Key Achievements:

✓ Architected automated ETL/ELT pipelines processing 50+ data sources daily

✓ Reduced operational monitoring time by 80% through AI-powered automation

✓ Implemented dimensional data models and real-time analytics dashboards

✓ Expertise in data quality frameworks, incremental processing, and cloud optimization

Background: Master's in Data Engineering & Data Science with foundations in mathematics, ML, and AI.

Driven by: Creating reliable, scalable data infrastructure that empowers data-driven decision-making.

Langues

Arabe
Bilingue ou natif
Anglais
Capacité professionnelle complète
Français
Capacité professionnelle complète

Préférences en matière de lieu de travail

Accepte de travailler sur site

Marrakech (jusqu’à 50 km)

UM6P– College of Computing
Summer Data Science Internship
juillet 2023 - septembre 2023 (2 mois)
Ben Guerir, MK, Morocco
– Developed machine learning and deep learning models to optimize MPI communication patterns for large-scale PDE solvers and Benchmarked more than 12 ML and DL models, contributing to a research paper published.
Data science Machine learning Deep Learning MLOps
DigitalProduction Center, UCA
end of study internship
HIGH TECH
avril 2022 - juin 2022 (2 mois)
Marrakech, MK, Morocco
Developed a full-stack web application using Spring Boot, Angular, and Docker-based microservices for financial services use cases.
Spring boot Angular Docker Java JavaScript
Value Driven Data
Data engineer
E-COMMERCE
novembre 2024 - février 2026 (1 an et 3 mois)
Dubaï, Émirats arabes unis
End-to-End Market Data ELT-ETL Pipelines on Snowflake
Designed, developed, and maintained end-to-end data pipelines using Snowflake, ensuring reliable, high-quality datasets ready for analytics and machine learning use cases.
– Leveraged Snowflake features (Data Warehouse, Streams, Tasks) to automate data workflows and manage incremental updates, collaborating with cross-functional teams to deliver weekly client requirements.
Automation & AI-Orchestrated Data Pipelines
Automated existing data pipelines using Apache Airflow, monitored DAGs, and integrated VM connections for seamless workflow orchestration.

Developed a Python/Pydantic AI control agent to validate pipelines and trigger corrective actions, reducing operational monitoring time by 80%.
Python Data Warehousing Apache Airflow Machine learning Data Engineer

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Bachelor Level
Bachelor Level
MSc
Mohammed VI Polytechnic University (UM6P)
2024
MSc

Consultez la formation qu'a suivie Mohamed

Mohamed Kiddi

Data ENGINEER/Data Scientist

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