Papa Mor Ndiaye

- Designed and implemented an automated system to reconcile financial transactions between Intouch and its external partners across 28 countries. - Developed custom data matching algorithms using Python to detect inconsistencies between internal and partner datasets. - Built ETL workflows using Apache Airflow, automating data extraction, normalization, comparison, and reporting for reconciliation . - Set up the full deployment architecture on Google Kubernetes (GKE) using Terraform, Helm, and GitLab CI, to ensure reproducibility and scalability. - Stored and analyzed large volumes of transactional data in BigQuery, enabling real-time anomaly tracking and reporting. - Added unit tests to critical Airflow tasks and validation steps to ensure data quality and process reliability. - Integrated Google Cloud Storage for managing and accessing partner files in CSV format across the reconciliation pipeline.

- Developed, maintained, and optimized a Batch Processing project to handle mass notifications for transactions using Javax Batch, ensuring high efficiency and scalability. - Worked on configuring and deploying platform services to ensure smooth integration with the backend systems and the cloud infrastructure. - Collaborated with the team to implement best practices for cloud-based infrastructure management on Google Cloud Platform (GCP). - Optimized the processing pipeline for large-scale transaction notifications, ensuring high availability and low latency.