Jason Leacox,
About Jason Leacox,
Jason Leacox is a Data Infrastructure Engineer at Semios in Vancouver, British Columbia, where he has worked since 2020. He has a diverse background in engineering and data management, with experience in various roles across multiple organizations.
Work at Semios
Jason Leacox has been employed at Semios as a Data Infrastructure Engineer since 2020. In this role, he focuses on scanning organization-wide for Personally Identifiable Information (PII) data using NodeJS and Data Loss Prevention (DLP) APIs. He also develops strategic and tactical cloud privacy and security initiatives, drawing on his extensive background in risk and compliance. His responsibilities include managing and auditing systems access across the Google Cloud Platform (GCP) ecosystem and regularly deploying production data pipelines using Prefect Cloud and Python.
Previous Experience
Before joining Semios, Jason Leacox worked at several organizations, including PwC Canada, where he served as a Senior Consulting Engineer in One Analytics for 11 months. He also held the position of Senior Sustainability Engineer, Data Analyst, and Innovator at PwC Canada from 2017 to 2019. Additionally, he worked as a Senior Risk Engineering Consultant and Manager at Atkins from 2010 to 2017. His experience includes developing custom connectors for external weather APIs and training junior engineers on deployment processes.
Education and Expertise
Jason Leacox earned a Bachelor of Science in Mechanical Engineering from The University of Calgary, where he studied from 2004 to 2009. His educational background provides a strong foundation for his technical roles. He has also engaged in self-directed learning, focusing on technical self-development from 2017 to 2020. His expertise encompasses data infrastructure, cloud privacy, security initiatives, and machine learning infrastructure.
Volunteer Experience
In 2021, Jason Leacox volunteered as a Machine Learning Infrastructure Volunteer at the Research AGI Organization for four months. This role allowed him to contribute to the development of machine learning infrastructure, further enhancing his skills in data management and engineering.