Backend Engineer
Ismail Nyza
Backend engineer focused on reliable backend systems, distributed workflows, clear technical communication, and production-minded execution.
I do my best work on backend systems that need to be dependable, observable, and straightforward to evolve. My experience spans Java, Go, Spring Boot, Kafka, PostgreSQL, Docker, AWS, and the operational details that make services hold up in production.
Backend systems, distributed workflows, platform-minded design, and engineering that survives real production pressure.
The build-in-public side lives separately in the grind page so this homepage stays clean, professional, and easy to evaluate.
About
I am a backend-first engineer who cares about services that are reliable under pressure, clear at the interface level, and sane to evolve after the first version ships.
Across product and platform work, I have built REST APIs, event-driven workflows, cloud deployments, database-heavy backend features, chat integrations, and the day-two engineering details that make backend systems worth trusting.
This homepage is the professional view. The deeper public grind, study trail, and weekly progress live on a separate page so the work and the proof can each speak clearly.
Experience
My recent experience spans backend engineering at Velosync and PickMe, plus earlier product and platform work across Golang, Java, Spring Boot, PostgreSQL, Kafka, React, GraphQL, and AWS-driven systems.
Featured Projects
Flagship backend systems built to demonstrate workflow coordination, platform thinking, durability, failure handling, and operational visibility.
Skills
Primary Focus
Java, Spring Boot, DSA, JVM internals, code review discipline
Backend Systems
REST APIs, event-driven workflows, multi-tenant architectures, reliability-oriented design
Internals To Sharpen
GC behavior, bean lifecycle, class loading, concurrency semantics, debugging under pressure
Data & Messaging
PostgreSQL, Kafka, Avro, Query Optimization
Reliability
OpenTelemetry, Prometheus, Testing, Debugging, Production Support
Cloud & Infra
AWS, EC2, Docker, Kubernetes, deployment discipline, service operations
Tooling Philosophy
Use AI as leverage, not as a substitute for understanding. Keep notes, proof, and architecture close.
Communication
Technical writing, recruiter-friendly framing, architecture explanations, build-in-public updates
Range
Go, React, frontend collaboration, AI experiments, and product work when the backend needs broader ownership
Public Work In Progress
The public layer around the engineering work: notes, explanations, experiments, and a visible record of what I am relearning.