Aleksey Gurzhiev

Aleksey Gurzhiev

Technical Product Manager & Product Architect

FinTech · Trading Systems · High-Load · Event-Driven

Available for onsite work in Dubai (Aug–Sep 2026) · Open to select opportunities worldwide

About

I am a Technical Product Manager and Product Architect with 15+ years of deep software engineering roots (Java/Spring, Scala, C/C++, Python). My expertise lies at the intersection of FinTech, algorithmic trading platforms, and high‑load B2B systems where reliability, low latency, and data integrity are non‑negotiable.

Unlike traditional Product Managers, I don't just manage backlogs; I understand system constraints at the architecture level. I bridge the gap between complex engineering realities and scalable business goals. Having architected live front‑office trading systems and exchange software, I know exactly how market data ingestion, signal engines, and order execution pipelines operate under the hood, and can translate quant/trader requirements into precise backend specifications.

My analytical foundation allows me to build end‑to‑end data workflows: from event modeling and data marts (ClickHouse, PostgreSQL) to orchestration (Airflow) and visualization (Grafana, Metabase). I run A/B tests, perform cohort analysis, and write production‑grade SQL and Python (pandas, scikit‑learn) daily.

Core Expertise

Technical Architecture

High‑load, low‑latency, event‑driven systems. Kafka, Kubernetes, Spring Cloud, microservices. Designing platforms that scale.

FinTech & Trading

Order books, matching engines, market data ingestion, risk management. Front‑office trading infrastructure.

Data & Analytics

Big Data pipelines, SQL, Python, A/B testing, BI dashboards. Turning raw data into product decisions.

Book

Book cover: Big Data, Digital Transformation & Machine Learning

Big Data, Digital Transformation & Machine Learning for Business Owners and Executives

Currently available in Russian · 2023

A practical guide for decision‑makers, explaining complex tech in simple terms. Written to help leaders understand how to invest in data without diving into code.

View on Litres

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