Python Developer • AI SDLC • Data Analytics • Data Engineering
I'm a professional trader with years of experience in the financial markets. While my day-to-day career is focused on trading, I have developed a strong passion for software development and data engineering — driven by a desire to solve real problems with code.
My projects reflect two things:
I've built production-grade data pipelines and interactive dashboards from scratch using Python and its ecosystem. I also leverage AI coding agents to architect and ship full-stack applications — combining domain expertise with modern AI-assisted development workflows.
I'm looking for opportunities in Data Engineering or Python Development where I can apply my analytical mindset, self-taught programming skills, and relentless drive to learn and ship quality software.
Background & motivation
My professional path started well outside tech, across trading, insurance, and business operations, where I developed strong analytical instincts, a structured approach to problem-solving, and confidence in making decisions under pressure. Over time, that foundation led me into programming and data work, because software gave me a practical way to turn complex processes into systems that are measurable, scalable, and easier to improve.
Today, that transition is being strengthened through formal engineering development. Through the EPAM Python Engineering program, I am deepening my skills in backend development, database design, cloud fundamentals, engineering standards, and AI-supported delivery practices in a professional, production-oriented environment. At the same time, I am participating in AI/Run Mission 2026: Build Your AI Factory, which focuses on building hands-on fluency in AI-powered software delivery, cross-role collaboration, and AI Factory ways of working aligned with EPAM’s Frontier-level AI maturity model.
What motivates me most is building practical tools around workflows I understand deeply. That has led me to create projects in trading analytics, football data, and automation, where I combine Python, SQL, dashboards, and full-stack development to solve real problems and turn raw data into useful insight. I am looking for opportunities in Data Engineering, Data Analysis, or Python development where I can keep growing as an engineer while contributing with ownership, curiosity, and a strong analytical mindset.
Technologies I work with across my projects
Real-world applications built from scratch
A locally deployed decision-support system for intraday Futures trading. Replacing a manual workflow with this platform reduced my daily preparation and review time from 2 hours to 15 minutes and increased my process goals completion by 40% by helping maintain focus on the right context.
The Python/FastAPI backend automatically ingests Sierra Chart exports and market data to generate self-contained HTML pre-market reports. During live sessions, a background poller evaluates the market regime via a weighted rules engine, displayed on a React/Tailwind SPA. Post-session, it imports trade logs and auto-tags them against session snapshots using SQLite feature-store rules.
End-to-end ELT pipeline for ingesting, modeling, and serving football statistics from the SofaScore API. Uses a medallion architecture (Bronze → Silver → Gold) orchestrated with Airflow, stored in MinIO/PostgreSQL, and transformed via dbt. Supports 20+ European leagues with both historical backfill and incremental daily updates. Produces 13 analytical mart tables for BI exploration.
A Streamlit-based web application for visualizing football analytics, team performance, match predictions, and league insights. Features multi-league support, interactive radar charts, head-to-head comparisons, form tracking, and league percentile rankings. Deployed live on Streamlit Cloud, connected to a PostgreSQL database populated by the data pipeline above.
A high-performance web dashboard for analyzing trading results, built entirely with AI coding agents. Features 16 key performance indicators, equity curves, calendar heatmaps, trade duration analysis, and an advanced tagging system. Demonstrates the ability to architect, direct, and ship a complete full-stack application by leveraging AI agents — from defining specifications and reviewing generated code to debugging and iterating on a production-quality result.
Consistent contributions across all projects
Interested in working together? Feel free to reach out.