Angel Alvarado

Angel Alvarado is a seasoned technical leader and data architect whose career spans full-stack web development, large-scale data engineering, and applied machine learning. With extensive experience leading cross-functional, globally distributed teams, he has built a reputation for delivering robust, scalable solutions across some of the most complex technical environments in the industry.

His core expertise lies in designing and implementing data pipelines and architectures that integrate across a wide range of modern platforms and technologies. Leveraging Python, R, Snowpark, and SQL, Angel has developed solutions that connect with tools including Snowflake, AWS, GCP, BigQuery, MySQL, Redis, MongoDB, Solr, and Elasticsearch — giving him a comprehensive, hands-on understanding of how modern data infrastructure is built and maintained at scale.

Beyond data engineering, Angel brings deep expertise in data visualization and analytics, working with platforms such as Hex, Tableau, Jupyter, Streamlit, and Superset to translate complex datasets into actionable insights for technical and non-technical stakeholders alike. This ability to bridge raw data and meaningful decision-making is a skill that directly informs his review work at OMC.

Angel began his career in full-stack web development and retains strong proficiency in PHP, Ruby, JavaScript, and shell scripting. This end-to-end technical range — from front-end interfaces to back-end systems and data infrastructure — gives him a uniquely comprehensive lens through which to evaluate program content covering the full spectrum of computer science and software engineering disciplines.