Hind Achniri

As part of the Stella project, a program aimed at migrating the legacy SICAP (Mainframe) information system to the new CLEVA information system, working within the SynchroRef team in a Scrum and SAFe environment. Responsible for the design, development, and production deployment of several application components: • Inter-System Synchronization : Developed a component responsible for synchronizing data between the SICAP and CLEVA information systems, based on an event-driven architecture and asynchronous mechanisms, serving more than 5 million customers. Addressed event loops, sequencing, and data consistency challenges. • Referential Mapping : Developed a component for mapping individual and legal entity identifiers between SICAP and CLEVA across various Groupe ProBTP partners, including BNP Paribas Cardif and MME. • Rejection Management : Developed a component for handling data rejected during synchronization, including a user interface enabling business users to view, analyze, and process rejected data. • SICAP/CLEVA Integration : Developed a set of REST APIs for searching, creating, and importing customers into SICAP from CLEVA. • Data Recovery Batch : Developed a daily batch process to reconcile Data Warehouse data, identify discrepancies, and automatically process unsynchronized data. • Recycling and Export Batches : Developed batch processes for Referential Mapping and automatic rejection recycling • Technical environment : Java, Spring Boot, Spring Batch, Spring Security, Hibernate/JPA, Stambia, PostgreSQL, Angular, Docker, Maven, Git, Jenkins, SonarQube.

Developed a microservice for a VPN solution responsible for user authentication, OAuth 2.0-based authorization, and role management. Technical environment: Java, Spring, Spring Boot, Spring Security, PostgreSQL, JUnit, Mockito, Docker, Maven, Bitbucket, Jira.

• Designed and deployed a real-time ETL and network monitoring system based on a microservices architecture, with Kafka-based data ingestion and processing. Integrated AI/ML-based anomaly detection to identify abnormal network behavior from processed monitoring data. Development of dashboards for network monitoring. • Technical environment : Java, Spring Boot, Spring Security, Apache Kafka, MySQL, Mockito, Docker, Maven, Angular, Grafana, Python, Jupyter Notebook, Pandas, NumPy, Scikit-learn, MCP (Model Context Protocol), LLM, AI Agents, REST APIs.

• Worked on modernizing traditional BOSCH wall scanners using AI and deep learning. • Implemented real-time data capture using a Raspberry Pi and Camera Module, and synchronized the captured data with other realtime data sources. • Technical environment : C++11, Python, Pybind11, Raspberry Pi, Raspberry Pi Camera, OpenCV, FFmpeg.