Mouad Merrouchi

Active participation in the design and implementation of large-scale data processing systems as part of the migration of the Data Warehouse to Microsoft Azure / Microsoft Fabric. — Contribution to the migration of the on-premise Data Warehouse to Microsoft Azure via Microsoft Fabric. — Development and maintenance of ETL/ELT pipelines for processing large volumes of data, reducing processing time by 40%. — Implementation of the Medallion architecture (Bronze – Silver – Gold) to improve data structuring. — Development of PySpark notebooks for transformation and quality control, increasing data reliability by 95%. — Creation of supervision dashboards in Power BI, enabling a 30% reduction in incident resolution time through real-time monitoring. — Participation in the automation of CI/CD deployments with Azure DevOps.

— Contribution to performance steering through KPI definition and creation of interactive dashboards (Microsoft Fabric, Power BI).

Designed and developed an interactive dashboard to monitor meteorological station data at global, national, and local levels. The solution enables tracking of data exchange, performance, and data quality through automated pipelines and structured data models.

Responsibilities

Built end-to-end data pipeline (API extraction, ETL processing, storage)

Integrated and stored data in MySQL database

Designed a star schema data model for optimized analytics

Developed interactive dashboards using Power BI (multi-level analysis: global → local)

Defined and implemented KPIs for performance monitoring and data quality

Automated data refresh and reporting processes

Technologies

Power BI, Python, API, ETL, MySQL, Data Modeling (Star Schema)

Results / Impact

Enabled real-time monitoring of meteorological data flows

Improved visibility on data quality and station performance

Delivered actionable insights through dynamic dashboards