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Paul Yu

Data Engineer

Data engineer with expertise in enterprise-scale data solutions that drive business value, specializing in Python, SQL, and modern data infrastructure. My focus is on transforming complex data challenges into reliable, high-performance systems while mentoring teams in technical excellence.

Technical Skills

Programming Languages

Python, R, SQL, HTML/CSS, TypeScript/JavaScript

DevOps and Cloud

Docker, AWS, Git, CI/CD (GitHub Actions), Nginx, FastAPI

Data Science and Engineering

Pandas, Numpy, Domo, PowerQuery

Frontend

React.js, NextJS, Remix, Tailwind, shadcn-UI

Professional Experience

  1. Data Engineer, Supervisor
    present
    Omnicom Media Group, Marketing Science

    Technical Leadership: As a technical leader and architect, I focus on three key areas: strategic system design, team empowerment, and operational excellence. I architect enterprise-scale data solutions that drive business value, while mentoring team members in best practices and innovative approaches. My role combines technical expertise with leadership skills to transform complex data challenges into revenue-generating opportunities.

  2. Data Engineer
    Omnicom Media Group, Marketing Science

    Technical Excellence: In this hands-on technical role, I specialized in building robust data infrastructure and maintaining high-performance systems. My focus was on technical excellence through precise implementation, systematic problem-solving, and continuous improvement of data pipelines. I combined deep technical expertise with analytical rigor to deliver scalable solutions that significantly improved operational efficiency.

  3. Data Analyst
    Publicis Groupe, Data Science

    Cross-functional Impact: As an analyst, I demonstrated strong collaborative abilities and analytical thinking. My role emphasized cross-functional partnership, translating business requirements into technical solutions, and delivering actionable insights. I developed a foundation in stakeholder management and project execution while maintaining high standards for data quality and analysis.

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