I am a backend and data-focused software engineer with 3+ years of experience building scalable, high-performance systems and data platforms. I have worked extensively with Go, Python, SQL, distributed systems, databases, ETL/CDC pipelines, and cloud infrastructure. My experience includes designing multi-tenant analytics platforms, real-time data pipelines, APIs, and data-intensive services handling large-scale workloads. I enjoy solving complex engineering and data problems, optimizing systems for performance and reliability, and building automation that improves developer and business efficiency. I am particularly interested in backend engineering, data engineering, distributed systems, and AI-powered data applications.
Bachelor's Degree
3-5 Years (Mid-Level)
Analytics Infrastructure: Built and optimized large-scale analytics pipelines processing 3.5PB+ data annually, 25T+ rows read, and 14B+ rows written.
Analytics Performance & Cost Optimization: Reduced CPU usage ~48%, data scanned ~34%, and infrastructure costs ~20% through query and pipeline optimizations.
AI-Powered Analytics Tool: Built an internal RAG-based analytics workflow using contextual retrieval and Tinybird MCP to help developers generate data queries, reducing on-demand analytics request time by ~50%.