About

From data warehouses to machine learning in production.

With over 15 years in the tech industry, I have evolved from a Data Warehouse Developer to my current role as Principal Data Engineer and MLOps Lead, specializing in modern data platforms and machine learning operations.

At Affirm / PayBright in Toronto, I've led the design and implementation of robust OLAP and OLTP databases on AWS and Azure. I architected scalable data pipelines, developed REST APIs in .NET C#, NodeJS and Python, and integrated with third-party services like Equifax, Stripe and Salesforce. These experiences honed my skills in building ETL/ELT workflows and delivering actionable insights using tools like Looker and Google BigQuery.

Currently, as an MLOps Lead, I focus on enabling scalable and efficient machine learning workflows with Azure Synapse and Databricks. My work involves automating and optimizing data pipelines for Big Data, ensuring reliability and scalability for production workloads. I oversee the deployment and monitoring of machine learning models, ensuring they seamlessly integrate with existing systems and deliver consistent performance.

My experience at Uptake, Globalive and Gemma Communications has given me a deep understanding of traditional software development, data engineering and the evolving field of MLOps. I am well-versed in Agile methodologies, using tools like JIRA and Confluence, and proficient with version control systems such as GitHub, GitLab and Bitbucket.

This diverse background in data engineering, MLOps, cloud infrastructure and automation equips me to drive innovation, optimize data platforms and ensure operational excellence in any tech-driven environment.