┌─────────────────────────────────────────────────────────────────────┐
│ │
│ ❯ whoami │
│ │
│ Name ── Pınar Topuz │
│ Role ── Full-Stack and Backend Engineer │
│ Focus ── Scalable APIs · System Design · Clean Architecture │
│ Stack ── Go · .NET 8 · Next.js · TypeScript · PostgreSQL │
│ Approach ── Architecture-first. Build systems, not demos. │
│ Location ── Samsun, Turkey 🇹🇷 │
│ Status ── ● OPEN TO WORK / ● BUILDING IN PUBLIC │
│ │
└─────────────────────────────────────────────────────────────────────┘
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I'm a Full-Stack and Backend Engineer who obsesses over system design, clean architecture, and developer experience. I don't just ship features — I build foundations that scale. My backend work revolves around Go and .NET 8, designing RESTful APIs and event-driven services that are both performant and maintainable. On the frontend, I craft polished UIs with Next.js and TypeScript — always with UX and performance in mind. Engineering values: Currently into:
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// engineer.go
package main
type Engineer struct {
Name string
Role string
Languages []string
Databases []string
DevOps []string
Mindset string
}
func NewEngineer() Engineer {
return Engineer{
Name: "Pınar Topuz",
Role: "Full-Stack and Backend",
Languages: []string{
"Go", ".NET/C#",
"TypeScript", "Python",
},
Databases: []string{
"PostgreSQL", "Redis",
},
DevOps: []string{
"Docker", "GitHub Actions",
"Vercel", "Nginx",
},
Mindset: "ship → measure → improve",
}
}
// Location: Samsun, Turkey 🇹🇷
// Status: ● open to work |
A full-featured auth system architected for real-world scale. Clean separation of concerns, middleware chain design, and a React frontend that communicates via typed API contracts. Highlights:
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A fully integrated CRM built design-first. Every screen was designed before a single component was written. The result is a cohesive product with a real user experience. Highlights:
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A reference architecture for production .NET APIs. Structured logging, health checks, containerization, and a CI/CD pipeline ready to drop into any team. Highlights:
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A research project combining domain knowledge with machine learning. ARIMA-based forecasting with custom feature engineering rooted in physical constraints. Highlights:
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"First, solve the problem. Then, write the code."
