Full Stack & Data Automation Engineer

Ibrahim is a Full Stack & Data Automation Engineer with a strong background in developing scalable web applications and optimizing data pipelines. He leverages modern frontend and backend technologies, alongside cloud platforms, to deliver robust and efficient software solutions.

Expertise

Full Stack Development

Expertise in building robust and scalable web applications from front to back, ensuring seamless user experiences and efficient data handling.

ReactNext.jsPythonFlaskNode.js

Data & AI Automation

Specializing in designing and implementing automated data pipelines, extraction tools, and leveraging AI/ML concepts for real-time insights and operational efficiency.

Python AutomationETLPuppeteerBeautiful SoupSQL

Cloud & DevOps

Proficient in deploying, managing, and optimizing applications on leading cloud platforms, with a focus on CI/CD, containerization, and infrastructure as code.

AWSGCPDockerGitGitHub Actions

IoT & Embedded Systems

Experience in designing and prototyping IoT solutions, including PCB layouts, hardware assembly, and integrating sensor data with real-time applications.

KiCad3D DesignRaspberry PiGPSFlutter

Selected Work

1 Projects

Smart IoT-Based Shared Bike System

Integrated a cross-platform Flutter application with a real-time Firebase datastore and automated operational alerting dashboards, enhancing system monitoring and user interaction.

Developed an intelligent mobility solution using Raspberry Pi, GPS, and accelerometer sensors for real-time tracking and theft detection.

Experience

2024

Led Odoo 18 deployment on AWS EC2, boosting system uptime by 40% and reducing latency by 30%.

2024

Engineered custom Python automations for Odoo, cutting manual workflows by 50%.

2024

Architected advanced data extraction and transformation pipelines on GCP, reducing reporting time by 80%.

2024

Designed production-ready IoT prototypes, including PCB layouts and 3D-printed enclosures, accelerating development cycles by 35%.

2023

Streamlined data acquisition pipelines, reducing manual effort by 70% and improving reliability from 60% to 95%.

2022

Optimized HFSQL queries and resolved system bottlenecks, improving database performance by 20%.