Simon

Ekelund

.NET · CMS · Full-Stack

Building what matters, with precision.

Available · Malmö, SE

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01 — About

The short
version.

I'm a .NET developer with around five years of hands-on experience in C#, backend architecture, and enterprise CMS platforms. I recently graduated and I'm currently studying Computer Science at MAU.

Before software, I spent years in fast-paced service environments — including one of Helsingborg's busiest venues. That's where I built Lagerkollen, a small inventory system that added bottle scanning during refills so stock could be tracked in real time. It started as a practical fix for a real problem on the floor.

Later I worked as a sales consultant for Elgiganten, focused on computers and gaming hardware — mostly translating technical detail into advice people could actually use.

These days I'm most interested in where backend engineering meets applied machine learning and agentic tooling: building things that are useful, not just things that look impressive.

Years experience

Primary language

Helsingborg, Sweden

Simon Ekelund · 2026

02 — Journey

How it
happened.

2019–21

First Contact

An interest in how things work beneath the surface became a conviction that this was the path. The decision to commit was quiet — but permanent.

2022

The Education

Started formal .NET development training. C# became the primary language. Learning to think architecturally — not just to make things work, but to understand why they work.

2023

Into the Industry

Internship at Concid. First professional exposure to enterprise CMS at scale — Optimizely and Umbraco. Real clients, real constraints, real code.

2024

Between Worlds

Graduated in .NET development. Continued working in a high-pace service environment while actively pursuing a role in software. Two realities running in parallel — neither one paused.

2025

Momentum

Enrolled in Computer Science at MAU. Built Lagerkollen — a stock management system designed around real operational workflows. Delivered a full redesign for SPG Metall: new product architecture and a rebuilt browsing experience from the ground up.

2026

Now

Training computer vision models for image recognition. Exploring autonomous 3D navigation using NavMesh-based spatial mapping. Pushing further into applied machine learning and systems thinking.

03 — Capabilities