Zakaria EL GAZI

Turning sports app data into actionable insights to drive product and business strategy. • Built end-to-end data models from Decathlon Coach, Outdoor, Pacer, etc. • Partnered with PMs to define and deliver key metrics Stack: SQL (Databricks), DBT, Airflow, Python (Spark), Git (CI/CD), Google Analytics, Amplitude

Optimized marketing analytics, automated data processes, and shaped data governance strategy. • Built dashboards from Facebook & Google Ads APIs (Python, Spark, Dataiku) • Automated workflows via API integrations (Tableau, Dremio, Dataiku) • Defined data access strategy across tools (FreeIPA, Ranger, Dataiku, Dremio) • Monitored app performance with ElasticSearch & Kibana • Change Data Capture with Debezium

Deepreach is an ad-tech that allows businesses to launch campaign on Deepreach app. Also, the app provides performance metrics from different medias • With the CTO : define the architecture, modeling system • Built data pipelines and reporting tools to track ad performance across major platforms. • Developed a custom Flask API & JS connector for Google Data Studio (GCP BigQuery) • Automated data collection from Facebook, Google, Snapchat & Waze APIs • Explored orchestration & transformation with Airflow + DBT Stack: Python (Flask), JS, BigQuery, Docker, AWS (EC2, Lambda, RDS), PostgreSQL, CI/CD, Looker

With Capgemini Worked on marketing data projects, industrializing machine learning models and managing large-scale data processing. Industrialized Python Spark algorithms and machine learning scripts on the Hadoop cluster • Collected business requirements and calculated aggregates • Performed data analysis with Hive/Impala (Hue platform) • Attended business workshops on deep learning Worked in an Agile environment Stack: Hadoop, Pyspark, Hive, Impala, Unix, $U, Git, Jira

Worked on reconstructing management control tools and automating financial data analysis processes. • Contributed to the reconstruction of management control dashboards after system migration (SAS) • Automated financial data analysis by building SAS datamarts, replacing manual Excel processes Stack: SAS Enterprise Guide (SQL + Macros)

Built KPIs, data warehouses, and explored data visualization tools to improve business insights. • Developed performance KPIs for various services using QlikSense & SAP BI 4 • Built a complete data warehouse and managed data storage with ETL Datastage • Conducted POCs on Tableau, SAP Lumira, and SAS Visual Analytics Stack: Oracle SQL Developer, DataStage, SAP Business Objects XI.4, QlikSense

- Implement training for MEL employees and supervisors. - Participate in the construction of new tools to offer simple and effective methods to facilitate the identification of needs. - Prospective watch on a training subject: new training technologies, distance training, efficiency of training methods, training and motivation of learning, cognitive development. -Interviews to specify specific training needs, drafting of CCTPs for public purchases, definition of internal internships, registrations for CNFPT or other organization internships, monitoring of attendance and evaluations, monitoring of purchase orders and invoices via the Neeva software.