Enes Özkan

Enes Özkan

Full Stack Developer. Designing reliable, distributed, and highly scalable web and mobile applications. Focused on building robust system architectures, high-performance backends, and seamless digital experiences using modern technologies.

Specialized in distributed systems and full-stack development, I design and implement scalable, maintainable solutions from core backend services to end-to-end application architectures, with a strong emphasis on performance, reliability, and clean system design.

Selected Work

  • GUIDE

    Advanced analytics platform for Shopify stores that delivers comprehensive sales insights, customer behavior analysis, inventory intelligence, and AI-driven recommendations to support data-driven business decisions and improve overall store performance.

  • Rezervly

    Developed a cross-platform mobile reservation application that enables users to discover businesses, book appointments, manage reservations, receive real-time booking updates, and streamline scheduling through an intuitive and user-friendly interface.

  • Thailand Arrival Card

    Developed a software solution that integrates with the Thailand Government's Digital Arrival Card system, automating form submission workflows, improving data accuracy, and simplifying the entry registration process for travelers.

  • Industrial Operations & Performance Analytics Platform

    Designed and developed an enterprise platform for production line monitoring, maintenance management, technical personnel performance tracking, personnel card analytics, and KPI-based operational reporting to improve maintenance efficiency and production performance.

  • London Bike Rides

    Performed large-scale data analysis on London's public bike-sharing dataset (2022–2023), uncovering usage trends, seasonal patterns, peak demand periods, and operational insights through statistical analysis and interactive data visualizations.

  • NPU & GPU-Based Real-Time Voice-to-Text for Windows

    Developed a high-performance Windows speech recognition application utilizing NPU and GPU acceleration for real-time voice-to-text transcription. The application provides low-latency offline speech recognition, live transcription, and seamless text input across desktop applications while optimizing hardware acceleration for maximum performance.