Renaud J. Beaupré

As the founding data engineer and analytics owner, I architect and maintain the complete data infrastructure supporting company-wide analytics, client deliverables, and strategic decision-making across 400+ clients in higher education including Harvard, Yale, UCLA, and Teach for America.

• ›Built enterprise-grade data lakehouse architecture implementing Type 2 SCD methodology on GCP, establishing BigQuery as the centralized data warehouse while integrating legacy systems and WordPress MySQL databases
• ›Created automated ETL pipelines using Cloud Build and event-driven architecture to ingest data from 15+ sources including HubSpot, Maxio, and Intercom, processing 10M+ monthly events with 99.9% uptime
• ›Implemented modern analytics engineering practices using dbt — 150+ tested data models with automated QA and Looker Studio dashboards delivering actionable insights to executive stakeholders
• ›Led Universal Analytics → GA4 migration for hundreds of properties ahead of Google's June 2024 deprecation deadline, ensuring zero data loss and protecting millions in client ARR
• ›Contributed to the company's AI Search product (LangGraph-orchestrated agentic RAG) and built an end-to-end observability framework using Langfuse evaluators and MongoDB Atlas to track user behavior and LLM cost attribution
• ›Deployed conversational analytics AI agents and agentic workflows on GCP, enabling non-technical stakeholders to query the BigQuery data warehouse directly via semantic layer in natural language

Co-founded an AI-powered business intelligence platform designed to help SMBs leverage LLMs and Generative AI in a cohesive manner.

• ›Designed and built a full-stack AI wrapper on the ChatGPT API — Flask backend with a CloudSQL database, HTML/CSS/JavaScript frontend — featuring shared information retrieval and prompt-engineered workflows for consistent, team-first AI responses
• ›Trained and mentored a junior frontend developer as their direct manager, providing technical guidance on architecture and best practices

Lead data engineer for the Performax initiative — a fixed-term data transformation project delivering actionable insights to BRP's global dealership network.

• ›Deconstructed complex Vistex SAP workflows into scalable medallion architecture designs for Type 1 and Type 2 SCD models using dbt with supporting Terraform infrastructure in Snowflake, delivering all milestones within the initial project timeline

Joined as a hybrid data scientist and analytics engineer tasked with modernizing data infrastructure and introducing data engineering best practices for an ecommerce subscription analytics platform.

• ›Migrated the company to a modern data stack, replacing ad hoc SQL with a dbt-based transformation layer and revamped subscription metrics architecture powering core BI products
• ›Built a CI/CD testing framework in GitHub for staging deployments, enforcing QA unit testing and DAG-based deployment validation to eliminate manual release risk
• ›Designed ETL pipelines in Stitch ingesting Shopify, Stripe, and third-party vendor data, and authored dbt contracts enabling external partners to consume core models directly
• ›Built customer and charge dimensional models in BigQuery and dbt with Looker dashboards, directly contributing to Skio contract renewal representing 30% ARR

Promoted from analyst to data scientist following Series B expansion, with the mandate to build machine learning-focused product lines around the company's ecommerce subscription offerings.

• ›Built XGBoost binary classification models for customer churn prediction and cross-sell segmentation using Python and Vertex AI, achieving a 12% performance improvement over baseline
• ›Deployed production ML models on GCP Vertex AI using Composer-scheduled jobs with CI/CD pipelines, exposing predictions via Snowflake API integration
• ›Created dbt models in Snowflake to track ML model performance via Looker dashboards and measure marketing campaign ROI using an A/B testing framework
• ›Developed a Linear SVC model using TF-IDF vectorized web-scraped data for multi-class merchant vertical classification, deployed with Docker and Kubernetes

Analytics lead across all business functions during company growth from $100K seed to $60M Series A.

• ›Automated KPI reporting (SQL/MySQL) across online and supply chain metrics, cutting manual reporting overhead by 90%, and built Looker dashboards blending transactional, psychographic, and geographic data for retail performance tracking
• ›Developed revenue forecasting models in Python and Jupyter Notebooks, and implemented A/B testing frameworks with Google Tag Manager for UI/UX experiments across primary and affiliate sites

First analyst hire on the Initium team as it worked to transform Sears.ca into a profitable digitally-native retailer.

• ›Automated reports using Google Analytics 360 and Google Sheets, reducing labor overhead by 10 hours/week, and collaborated with the data science team to build the company's first cloud database