Ahmed Ben Debba

• Designed the end-to-end event tracking architecture (schemas, standards, coordination with frontend/backend), and delivered scalable streaming pipelines on Dataflow/PubSub powering real-time analytics

• Owned the company's core data platform by leading ingestion, transformation, and real-time event pipelines,

improving reliability and reducing processing costs across Airflow/Cloud Composer

• Implemented GDPR-compliant user data lifecycle processes (deletion, anonymization, access) and deployed

monitoring/alerting (Grafana, Cloud Monitoring) to ensure daily pipeline operational health

• Built batch + streaming data flows powering CRM operations in Braze, translating marketing requirements

into robust, production-ready data architectures

• Designed and maintained large-scale ETL pipelines on Airflow/Cloud Composer, improving data reliability

and supporting group-wide analytics workloads

• Architected cloud data lakes and warehouses on BigQuery and Cloud Storage, enabling performant

SQL/NoSQL analytics and reducing query latency across teams

• Built, containerized, deployed, and monitored ML models in production using Docker, Kubernetes, CI/CD, and IaC, accelerating iteration cycles and model deployment speed

• Defined cloud infrastructure using Terraform and GitLab CI, standardizing deployment processes and improving platform scalability and operational efficiency

• Built distributed Spark pipelines processing millions of connection events daily, improving data throughput

and reliability across the analytics platform

• Designed cloud-based analytical databases and developed production-ready APIs with Flask, enabling

real-time access to campaign performance metrics

• Developed and deployed machine learning models (Scikit-learn, TensorFlow) in production, enhancing

predictive capabilities for advertising attribution