About Me
Software engineer with 20 years of experience specializing in large-scale data engineering, high-performance backend systems, and low-level optimization. Currently at Apple Media Products, I architect systems processing billions of events daily (multiple terabytes) using Spark, distributed databases, and stream processing.
My expertise spans the full stack—from assembly and C to modern distributed systems. I've built fault-tolerant microservices with event-driven architectures, optimized queries on terabyte-scale datasets, and developed performance-critical computational libraries. My career has evolved from Windows applications with C# and SQL Server to architecting complex data pipelines using Scala and Spark at scale.
I'm a power user of GenAI tools, leveraging LLMs not just for code generation but as force multipliers for optimizing workflows, system design, and technical problem-solving. I treat AI as another tool in my engineering toolkit, applying it strategically across the development lifecycle to enhance productivity and decision-making.
I'm passionate about performance optimization, utilizing concurrency and non-blocking algorithms to maximize modern hardware capabilities. My deep understanding of memory models across Java, C++, and Rust enables me to build systems that prevent race conditions and ensure data integrity through optimistic locking and speculative execution.
I'm currently focusing on Rust, building projects across backend services, data engineering, embedded systems, and GPGPU applications. What draws me to Rust is how naturally it aligns with my engineering philosophy: zero-cost abstractions, memory safety without garbage collection, and performance by design.