Full-Stack Software Developer. May 2026 to now. Toronto.
Sanofi
I work across two teams, CX Data & AI and Commercial M&S. Day to day that is React and Python on top of Snowflake, running on AWS, with Power BI for reporting. I also help ship web releases, which move from dev through UAT to production.
- people using Newton
- ~700
- messages a day
- ~500
- teams on the platform
- 5
- data sources unified for CX
- 15+
Newton, Talk to Data
Sanofi's company-wide platform for asking data a question.
Someone asks. Snowflake agents work out the SQL, run it, and come back with results and charts. I ship full-stack features across the platform.
Shipped so far
- Microsoft Graph access groups
- Prompt library
- Agent selection
- File upload
- Skills
- Data refresh
- Chat UI and prompt libraryWhat people see
- Access via Microsoft GraphWho can see which data
- Agents that write the SQLQuestion in, query out
- SnowflakeWhere the data lives
TraceReview, led end to end
One screen that shows what an agent actually did.
I scoped it with the agent owners, built it in React and Python, and shipped v1 in two weeks. For every run it lays out the agent's reasoning, the SQL it wrote, the results, and the charts.
- ~60% less time spent debugging agents
- ~5 production incidents caught
- Started as a Newton-only tool. Now any team can use it: 2 teams do today, and RUSH is joining
- Helped migrate it onto AWS
- 1Read the question and pick the right table.
- 2Check which columns answer it.
- 3Write the query, run it, then chart the rows.
Run timeline
Web releases
I help get each release to production.
Releases move from dev, through UAT, to prod on a cycle, and a different group of people runs each one. I help with that.
CX Data & AI
15+ sources, one database.
Automated ETL pipelines pull SharePoint, Google Analytics, and internal systems into a single database behind the team's React and Power BI dashboards.
What I work in there
- React
- Python
- Snowflake
- AWS
- Power BI
- SQL
- Microsoft Graph
- SharePoint
- Google Analytics