Gabriel Margonato

Data Analytics Engineer with 9 years of experience translating leadership needs into data models, pipelines, and cloud architectures. Experienced across AWS, Azure, dbt, and Databricks, with background in data governance, KPI standardization, and enabling self-service analytics through Power BI and Tableau dashboards, as well as ad-hoc analysis and data storytelling.

Senior Data Analytics Engineer at Global University Systems North America (2023-03 – Present)

Led the design and implementation of a cloud-based analytics platform, consolidating distributed global recruitment data into a unified Redshift warehouse, establishing a scalable foundation for reporting and analytics across US and Canada teams.

• Led the design and implementation of a cloud-based analytics platform, consolidating distributed global recruitment data into a unified Redshift warehouse, establishing a scalable foundation for reporting and analytics across US and Canada teams.
• Delivered executive Power BI dashboards tracking student acquisition funnels, conversion rates, and regional performance, defining and standardizing KPI logic used by leadership across partner colleges and universities.
• Built and maintained dbt models and ELT pipelines integrating DynamoDB, S3, and RDS sources, transforming raw data into structured, analytics-ready datasets for downstream consumption.
• Partnered with stakeholders across admissions, marketing, finance, and operations to translate business requirements into data models supporting performance tracking, forecasting, and strategic decision-making.
• Mentored junior analysts and engineers, coordinating task prioritization and promoting best practices in ETL workflows, SQL, data modeling, and analytics engineering workflows.

Instructor (Part-Time) at Fleming College Toronto (2023-09 – 2024-04)

Taught SQL and Python through project-based modules and created 'Storytelling with Data' workshop.

• Taught SQL and Python through project-based modules on the Introductory Computing course.
• Created and led 'Storytelling with Data', a workshop on presentation techniques for non-technical audiences, helping learners frame analytical results.

Data Engineer at Nestlé Health Science (2022-01 – 2022-08)

Architected and maintained an Azure-based Delta Lakehouse integrating ERP, e-commerce, and operational data, enabling scalable analytics across commercial and manufacturing domains.

• Architected and maintained an Azure-based Delta Lakehouse integrating ERP, e-commerce, and operational data, enabling scalable analytics across commercial and manufacturing domains.
• Built batch and real-time data pipelines in Azure Databricks using Spark and Event Hubs, supporting both transactional analytics and factory sensor monitoring.
• Designed data transformation layers aligned with Medallion architecture principles, structuring raw data into curated datasets for downstream reporting and analysis.
• Improved reliability and observability of data workflows through structured logging, monitoring, and pipeline optimization.

Junior Data Analyst at Itaú Unibanco (2017-03 – 2021-11)

Automated legacy reporting workflows and contributed to cloud migration initiatives while developing data models for insurance and fraud monitoring.

• Automated legacy Excel and VBA reporting workflows using Alteryx, SAS Enterprise Guide and SQL-based data pipelines.
• Contributed to migration of on-premise reporting systems to AWS cloud infrastructure.
• Developed structured data models to support insurance/fraud monitoring dashboards and operational analytics.
• Optimized SQL query performance and reduced manual data preparation through reusable transformation processes.

PGD in Artificial Intelligence, Development and Implementation – Georgian College (2023-04)

PGD in Data Mining and Analytics – FIA Business School (2022-01)

BS in Computer Science – Mackenzie Presbyterian University (2018-12)