Tingni Li

Key Achievements: - Designed and launched a secure internal platform (Flask, Bootstrap) automating coupon and SIM card workflows, supporting over 10 million cards annually for nationwide operations. - Built robust RESTful APIs with strong access control, real-time status tracking, and full audit compliance. - Developed and maintained large-scale ETL pipelines (Spark, Airflow) processing 50M+ records per day, deployed on a private cloud (VMware) with object storage (MinIO, AWS S3-compatible) and orchestrated via Kubernetes for scalable, resilient operations. - Re-architected a legacy ETL system into a modular, object-oriented framework supporting multi-format ingestion and 600+ business rules; implemented a self-service dashboard for business teams to manage imports, reprocess data, and monitor exceptions. - Led the migration to microservices, deploying production systems with Kubernetes and Harbor, enabling automatic failover and elastic scaling in a private cloud context. - Built real-time data monitoring solutions with Spark, Parquet, and ELK stack, supporting complex rules and providing unified logs, alerts, and incident management. - Optimized SQL data models (PostgreSQL, Redis) to cut dashboard load times from 2 minutes to 2 seconds. - Established CI/CD pipelines (GitLab) for automated testing, deployment, and monitoring, achieving zero-downtime releases in a private cloud/VMware environment. Team & Collaboration: - Worked in an agile team of 4, participating in weekly sprints, daily standups, and code reviews. - Collaborated closely with data analysts, product owners, and business users to deliver features aligned with real-world needs. - Promoted best practices in automation, documentation (OpenAPI/Swagger), and performance optimization across the team.

● Intégré les capteurs IoT nouveaux arrivés, les suivis régulièrement et enregistré ces changements (notamment sur les aspects autonomie d’énergie, qualité de connexion radio, gestion de mobilité …) ● Développé en Python des fonctionnalités de traitement des données collectées par nos capteurs ● Crée une base de données en utilisant SQLite afin de gérer nos capteurs ● Crée un page WEB partage selon notre base de données (React.js, SpringBoot) ● Proposé des améliorations faisables sur la plateforme monitoring des capteurs qui devra déployer au client et géré sa base de données via API ● Fourni les retours sur les problèmes ou les changements liés aux capteurs testés