Hello, I’m Moayad.
Software Engineer | Full-Stack, Big Data & Analytics

I currently work at Neuland - Büro für Informatik, a software development and consulting agency, where I contribute to a range of e-commerce projects.
My experience in cross-functional teams makes me an excellent choice for challenging projects that push technological boundaries and foster continuous skill improvement. I am eager to apply my knowledge and empower others to achieve collective excellence.

Expertise

Software Development

Proficient in structural, object-oriented and functional programming. Highly skilled in frontend and backend development, with particular expertise in software architecture, design patterns, and clean code principles.

DevOps

Experienced in CI/CD pipelines, infrastructure as code, containerization, and orchestration. Proficient in cloud computing, source control, and collaboration platforms, with a strong focus on automation, monitoring, and security.

Data Engineering

Skilled in data modeling, ETL pipelines, and stream processing. Experienced in data visualization and statistical data analysis, with a extensive knowledge on data quality and privacy.

Agile Methodologies

Experienced in Scrum and Kanban frameworks. Proficient in project management tools, with a strong focus on collaboration, communication, and continuous improvement.

Professional Experience

2023-now
Senior Software Engineer
neuland – Büro für Informatik GmbH. Bremen, Germany
2019-2023
Software Engineer
neuland – Büro für Informatik GmbH. Bremen, Germany
2019-2019
Data Analyst - Work Study
BIK - University of Bremen. Bremen, Germany
2018-2019
Research Assistant - Automation
BIME - University of Bremen. Bremen, Germany

Over five years of experience in software engineering, data science, and DevOps, working in multi-cultural environments and contributing to diverse projects of varying complexity and scale. I have a proven track record of delivering high-quality software solutions that meet business requirements and exceed customer expectations.

Linkedin
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Portfolio

Time-tracking Data Exporter

Developed a robust Command-Line Interface (CLI) designed to synchronize time-tracking data between Amazing Marvin and ActiTime . This project showcases my ability to integrate and automate workflows, ensuring seamless data transfer and enhancing productivity.

Key features include automated synchronization of task time-tracking data from Amazing Marvin to ActiTime , exporting time durations for a predefined set of tasks directly to ActiTime , and tracking daily overtime while generating CSV reports to monitor overtime balance.

Open Project

Distributed Computing for Real-Time DSP Applications

This thesis, conducted at the University of Bremen, shows how to distribute Digital Signal Processing (DSP) graphs across a cluster of computers. It presents a method to manage these graphs within a local network, ensuring automatic data synchronization.

The evaluation confirms the approach’s efficiency and scalability. This work provides a foundation for future research, suggesting enhancements and optimizations. The findings are relevant for organizations aiming to use distributed computing for real-time signal processing.

Petri-net Simulator

A web-based simulator for elementary nets. Elementary nets are a specialized form of Petri nets, which are powerful tools used to mathematically describe and analyze concurrent systems.

This simulator not only allows users to visualize and interact with these nets but also provides insights into the behavior and dynamics of complex systems. By leveraging this tool, users can model, simulate, and optimize processes in various domains such as manufacturing, logistics, and software engineering.

Open Project Live Demo

Natural Language Classifier Based on Reddit Posts for Information Retrieval

This work, conducted at the University of Bremen, aims to interpret user input by leveraging textual clues embedded within the data. Utilizing a dataset collected from thousands of Reddit posts across three subreddits (politics, datascience, listentothis), we analyze the implications of the chosen classifier for training these datasets.

Furthermore, we discuss how this classifier proved to be optimal for our work compared to other classifiers.

Certifications

2024
Certified Professional for Software Architecture
iSAQB
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2020
Introduction to Game Development
Coursera
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Education

2020-2023
University of Bremen
Computer Science B.Sc.
2017-2020
University of Bremen
Systems Engineering