Ben Njima Saber

SEB Group:

• Migrated data workflows from batch to real-time processing for smart coffee machines telemetry using Azure Data Explorer and streaming integrations, improving data freshness and decision latency for clients.
• Developed and optimized data pipelines in Azure Data Factory to process structured and semi-structured telemetry data efficiently.
• Improved client-facing KPIs by enhancing data accuracy, reducing latency, and ensuring reliable delivery of metrics for dashboards and analytics tools.

Technical Stack : Azure Cloud (Azure Data Explorer, Azure Data Factory, Azure Devops),KQL, Github, Jira

Panzani :

• Designed and implemented ETL processes in Azure Data Factory to clean, standardize, and transform SAP data, ensuring accuracy and consistency across business units.
• Led a data quality improvement initiative for international supply chain branches, defining naming conventions, validation rules, and best practices to improve data governance and integrity.
• Collaborated with project managers and business stakeholders to understand data requirements and design efficient deployment and transformation strategies aligned with business goals.

Technical Stack : Azure Data Factory, SQL Server, Azure Data Lake Storage, KQL, Github, Azure Devops

Twister DSI :

• Built Power BI dashboards to monitor key HR KPIs and workforce trends
• Designed data models and DAX measures for accurate and reliable reporting
• Implemented a RAG-based generative AI solution enabling natural-language access to HR data
• Stored and indexed data in a vector database to support semantic search and AI responses

Technical Stack : Power BI, DAX, Python, LangChain , Vector DB, GitHub, Docker

BNP Paribas, Datalab

• Ingested data from multiple APIs and SFTP servers into Google Cloud Storage Cleaned and transferred data from GCS to BigQuery using Cloud Functions and Apache Airflow
• Performed data transformations and created aggregation and exposure tables using scheduled queries in BigQuery
• Built interactive dashboards and reports with Google Data Studio to visualize business insights

Technical Stack : GCP, Cloud Functions, BigQuery, Airflow, Supermetrics, Python, Looker, Terraform, GitHub

FNAC DARTY

• Led the redesign and migration of customer data to Google Cloud Platform (GCP)
• Built batch data ingestion pipelines using Talend for Big Data from multiple heterogeneous sources
• Developed and optimized Spark (PySpark) jobs for data transformation, cleansing, and scalability
• Performed data transformations and analytics using BigQuery and SQL
• Managed, maintained, and documented Data Lake and Data Warehouse environments

Technical stack: GCP (Cloud Storage, BigQuery), PySpark, Talend for Big Data, SQL, HDFS, Hive, HBase, Jira