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Shifra M.
Bio
Detail-oriented and highly motivated developer with strong system thinking, fast learning abilities, and advanced problem-solving skills. A dedicated team worker who consistently meets deadlines, takes full responsibility for every task, and thrives in both independent and collaborative environments. Committed to continuous self-learning and delivering high-quality, reliable results.
Skills
Python
C++
C
Node.js
.NET
React
TypeScript
PostgreSQL
Kafka
Docker
Redis
WebSockets
Bootcamp Project
Workflow - A multi-tenant, dynamic management system for entities, events, workflows, and real-time operations.
Mentored by: Kaltura
Backend Bootcamp 2025 (Backend)
Responsibilities:
Designed and delivered the full Action-Creation Pipeline, a distributed, event-driven workflow enabling creation, validation, persistence, and preparation of Actions using NestJS, Kafka, .NET workers, and PostgreSQL.
Developed the Validation Worker, ensuring real-time atomic uniqueness checks, schema validation, and configuration integrity. Replaced DB-based validation with a distributed Redis lock using SETNX to eliminate race-conditions and reduce database load.
Designed the system’s relational data model (ERD), covering actioncatalog, processactions, actioncondition, actionschedules, and action_run, with proper foreign keys, indexing, and structures optimized for workflow expansion.
Developed React UI components and multi-step wizards for creating and managing workflow actions, including catalog selection, condition configuration, and scheduling flows.
Click to enlarge
Additional Projects
2025 | ExtraTech | SC&M – Services Control & Monitoring System
Developed a cross-platform monitoring system (Linux & Windows) for Moodle, VPL, and backup servers. Implemented a global scheduling engine using Python (APScheduler), built a heartbeat-based crash-detection mechanism, and designed the full SQL data model for metrics, crashes, heartbeat logs, and scheduled tasks.
2025|Smart Diet Management System
Built a full-stack nutrition management system that generates personalized weekly diet plans based on user food preferences . Implemented a greedy-based recommendation algorithm that selects the most suitable products for each user, ensuring alignment with their preferred food categories and diet type. Developed the backend in C# (.NET Core) with a clean layered architecture, and designed SQL Server schemas for users, products, preferences, diet types, and weekly tracking. Created a React interface for managing preferences and displaying tailored recommendations.
English Level
Working Proficiency