Hamza Khattabi

• • Resolved a Tier-1 production incident impacting 3M+ users by migrating a failing on-prem Kafka synchronization service to a scalable Azure Function written in Java; reduced consumer lag by 95% and increased message throughput by 3x to successfully restore and stabilize critical sign-up and sign-in flows.

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Architected and implemented a high-throughput data pipeline using Spring Batch to export millions of records from OracleSQL.

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Actively participated in architectural workshops to design cost-effective and high-performance Azure Cloud solutions. Developed a specialized synchronization engine with Azure Functions and Docker for financial documents between multiple CRM platforms, ensuring data integrity and compliance.

• • Contributed to the performance scaling of a flagship product by re-engineering core application processes, reducing latency, and enhancing the overall processing speed of our modulith application.

• • Managed production incidents by implementing data-driven monitoring and automated fixes. Worked in a full Agile environment, upholding high standards through rigorous code reviews, automated testing, and CI/CD best practices.

• • Ensured cross-environment consistency and rollback procedures through service pack and Liquibase migration.

• • Leveraged Terraform to design and deploy scalable AWS environments for Java Spring Boot applications.

• • Streamlined deployment workflows for EMA-related projects, ensuring environment consistency and infrastructure reliability across CI/CD pipelines.

• • Develop & maintain commission management system for independent agencies

• • Engineered a robust data processing engine using Spring Batch to compute and manage large-scale commission datasets for independent agencies, ensuring high throughput and transactional integrity with Hibernate & JPA for financial calculation

• • Led the migration of the core system from Java 8 to Java 21, utilizing modern features like Virtual Threads to handle challenging performance requirements and improve resource efficiency.

• • Optimized data-heavy operations by implementing efficient chunk-based processing and multi-threaded steps within Spring Batch to meet strict processing windows.