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Malka H.
Bio
A trained software developer specializing in AI technologies, highly motivated and capable of independent learning. Possesses strong mathematical, analytical and logical thinking skills. Curious and enjoy challenges, with a strong focus on attaining knowledge and engaging in deep thinking. Demonstrates excellent interpersonal communication skills and thrive on constructive interaction with superiors and colleagues.
Skills
Python
.NET
React
TypeScript
PostgreSQL
Kafka
MinIO
MQTT
Docker
Grafana
PyQt6
FFmpeg
Cron
REST API (Flask)
Matplotlib
Angular
Bootcamp Project
Sound - Cloud-based platform for agricultural data management and analytics
Mentored by: Vast Data
Data Science Bootcamp 2025 (Data)
Responsibilities:
Implemented Kafka startup logic inside Docker, including broker initialization, readiness checks, automatic topic creation with custom retention settings, and smoke-test validation to ensure message delivery functionality.
Implemented a fully automated audio-compression and tiering system that identifies old audio files based on the timestamp embedded in the filename, downloads them from MinIO, compresses them using FFmpeg (Opus/FLAC), replaces the original files with the compressed versions, removes outdated compressed files, and executes continuously through a Docker-based Cron scheduler.
Implemented data visualization inside the PyQt6 application by generating analytics graphs with Matplotlib and embedding them directly into the GUI views, while also integrating live Grafana dashboard panels through QWebEngineView to display real-time system metrics as part of the application's interface.
Developed a full notification-scheduling service including a Flask REST API with PostgreSQL persistence, supporting creation, editing, and deletion of scheduled tasks. Integrated the API with both a JavaScript web interface and a PyQt6 desktop view to provide a unified UI for managing schedules across the system.
Built a pipeline that ingests edge-device metadata via MQTT into Kafka, Flink, and PostgreSQL, while raw data files flow through Kafka, MinIO, bucket notifications, Flink, and PostgreSQL. Added a matching script that links data files with their metadata in a connection table, ensuring downstream use only of files that contain both.
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Additional Projects
A real-time AI-based SaaS platform for personalized recipes creation and organization.
Engineered the platform's interfaces using React 19 for the client side and Angular for the administration dashboard. Built scalable backend microservices with .NET Core and Python to process personalization logic and automated email notifications. Managed data persistence via MySQL, and implemented AWS S3 for cloud-based file storage. Secured user access by integrating Google OAuth and JWT mechanisms, while maintaining code versioning with Git.
English Level
Working Proficiency