About
Senior Systems & Data Engineer with a rigorous foundation in Applied Mathematics. Over seven years, I have architected high-performance data ecosystems and cloud-native infrastructure across GPU-accelerated clusters, distributed data lakes, and real-time medical data platforms.


Motto: Free markets, free people, free minds.
I specialize in mathematical system modeling, algorithmic latency optimization — specifically through vectorization, time-series decomposition, and high-performance computing (HPC) structures — and designing resilient distributed architectures. I deliver the highest impact in lean, collaborative engineering teams that prioritize deep technical focus, rigorous design documentation, and peer-to-peer growth.
Engagement
Where I Can Be Useful
Engagement boundaries & alignment.
I partner with engineering teams and technical founders when systems require core architectural decisions or a complete reliability overhaul. I operate as an architect-partner to deliver high-impact infrastructure, not to clear routine tickets.
I design scalable infrastructure foundations from scratch, optimize high-load pipelines through mathematical modeling, decouple monolithic architectures into distributed systems, and collaborate closely with founders to solve isolated, high-stakes technical bottlenecks.
I step aside from routine maintenance projects lacking modernization roadmaps, environments without clear engineering ownership, and organizations that prioritize rigid process bureaucracy over systemic engineering outcomes.
My Library
Featured Work

Pipeline Acceleration and System Observability
Meteorological data analysis (SODAR, meteorological masts) was bottlenecked by critical inefficiencies in time-series processing pipelines. Concurrently, operational blind spots within GPU-accelerated Kubernetes clusters caused unacceptable delays in system failure localization.
Executed a mathematical refactoring of critical Airflow DAGs/Celery workers, implementing vectorized algorithms via NumPy. To eliminate operational blindness, architected and deployed an enterprise-grade observability stack (Grafana, Loki, Prometheus), enabling real-time telemetry for GPU-accelerated clusters.
5–10xthroughput acceleration in pipeline execution, directly unblocking engineering decision-making processes. Radically reduced Mean Time To Resolution (MTTR) for incidents through transparent infrastructure monitoring.
Career Timeline
Got a hard problem?
I work with startups and technical teams building things that matter. Drop a brief — what's broken, what you're building, or what foundation needs to be laid right.





