Mark Chang
About Mark Chang
Mark Chang is a Senior Data Engineer currently working at Vpon Big Data Group in Taipei, Taiwan. He has extensive experience in data engineering, having previously held positions at various companies and achieved significant cost savings and efficiency improvements through his technical contributions.
Work at Vpon Big Data Group
Mark Chang has been employed at Vpon Big Data Group as a Senior Data Engineer since 2021. In this role, he has contributed to various data engineering projects, focusing on optimizing data storage and processing. His responsibilities include managing data pipelines and enhancing the efficiency of data operations within the organization.
Previous Experience in Data Engineering
Prior to his current position, Mark Chang worked at several companies in the data engineering field. He served as a Data Backend Engineer at BIG DATA Co., Ltd. from 2018 to 2020 and as a Data Engineer at CloudMile from 2020 to 2021. His earlier experience includes a role as a Software Engineer at 財團法人資訊工業策進會 from 2017 to 2018 and as an intern at the same organization from 2015 to 2017.
Education and Expertise
Mark Chang holds a Master's Degree in Engineering Science with a major in Information Technology from National Taiwan University, where he studied from 2015 to 2017. He also earned a Bachelor's degree in Management Information Systems from National Chung Cheng University, completing his studies from 2010 to 2013. His educational background provides a strong foundation for his work in data engineering.
Technical Contributions and Projects
Mark has developed a distributed Google Maps web crawler using Go language, which was deployed on GCP Cloud Run. This project resulted in significant time savings and an 86% cost reduction compared to traditional methods. He also enhanced information security through monitoring and logging systems, aiding in the company's ISO 27001 certification. Additionally, he optimized the GCP BigQuery data storage model, leading to monthly savings of $2400.
Process Optimization and Efficiency Improvements
In his roles, Mark has implemented various optimizations that improved operational efficiency. He utilized Terraform for cloud infrastructure management, achieving a 96% reduction in audit log search time. He also refactored BigQuery SQL scripts, resulting in a 75% reduction in query expenses and managed an Airflow upgrade plan that led to a 75% decrease in data pipeline development time.