CDPQ
2022 – 2025
Data engineering and full-stack application development for one of Canada's largest institutional investors.
Overview
Embedded within CDPQ's data engineering team, delivering Python-based data solutions, cloud migrations, and full-stack applications across the organization's investment analytics and fixed income divisions.
Key Contributions
Enhanced and maintained a Python data solution in a legacy Airflow environment using SQL Server and Snowflake databases.
Implemented a Python solution for the analytic fixed income team, adapting it to CDPQ guidelines while establishing comprehensive standards to optimize performance and ensure consistency.
Orchestrated the migration of existing solutions to Managed Workflows for Apache Airflow (MWAA) with Snowflake data handling.
Created a Python-based web application using Streamlit and S3, significantly accelerating analysts' daily report validation processes; deployed the application to Kubernetes using Helm charts, GitLab CI, and GitLab container registries.
Developed an Angular application with a Python FastAPI backend deployed to AWS using ECS, ECR, and Azure DevOps, that models capital injections into various funds for director-level oversight.
Built a real-time Bloomberg fixed income pricing application (Angular + C#) — a critical system used daily by traders to receive alerts on orders placed by the investment team.
Years of continuous delivery
Production applications shipped
Full Airflow migration completed