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About Me |
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I am a Staff Software Engineer specializing in distributed systems and backend infrastructure. With over a decade of experience in the fintech and blockchain sectors, I design high-throughput, event-driven platforms.
My core focus is scaling asynchronous processing, standardizing cloud deployments, and building fault-tolerant data pipelines using Python, Go, Kafka, and Kubernetes.
Languages:
Databases
Backend & APIs:
Distributed Systems & Infra:
Observability
- Simplicity over abstraction: Complex systems fail complexly. I heavily favor readable, maintainable architecture over "clever" engineering.
- Observability is a feature: You cannot scale what you cannot see. Metrics, tracing, and structured logging must be built-in from day one.
- Pragmatic scaling: Design the architecture to be horizontally scalable from the start, but delay heavy algorithmic optimization until proven by production bottlenecks.
- High-Throughput Backends: Designing event-driven platforms (Go/Python/Kafka) capable of processing millions of async tasks without deadlocking.
- Data Infrastructure: Architecting distributed ETL pipelines and analytics platforms using Airflow, ClickHouse, and Postgres.
- AI Backend Infrastructure: Exploring and integrating vector databases and scalable backend patterns to support AI-driven features and RAG pipelines.
When I step away from the keyboard, I prioritize endurance and continuous learning. I enjoy reading, cooking, cycling, hiking, learning guitar, and strength training. I’m always curious about exploring how complex systems, both in software and in life, can be made simpler and more reliable.