Notion
Software Engineer, Product Analytics Platform
About this role
Join Notion's Data Product Platform team to design and operate foundational systems powering features like search, automations, and AI. You'll work across the full stack with product, data science, and engineering teams to build scalable, event-driven platforms that enable millions of users to work faster and smarter.
What you'll do
- Own development of systems, tools, and infrastructure for data-powered product experiences
- Work cross-functionally with Product, Data Science, Data Engineering, and AI teams
- Build across infrastructure, libraries, and product code to deliver high-leverage internal platforms
- Monitor, operate, and optimize critical production systems with minimal disruption
- Design ergonomic APIs and tooling to help other engineers move faster
What they're looking for
- Full-stack system design and optimization
- Data-driven debugging using metrics, traces, and logs
- Infrastructure and platform engineering
- Event-based systems and data architecture
- API and developer tooling design
- Cross-functional collaboration
- TypeScript and Node.js (preferred)
- Production systems monitoring and operations
Benefits
- Competitive cash compensation ($196,000 - $261,000 base in San Francisco)
- Equity
- Comprehensive benefits package
- Work on products used by millions globally
- Collaborative, craft-focused team culture
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Notion
Notion builds an AI-powered collaborative workspace platform used by millions for productivity, featuring capabilities like search, automations, and AI-assisted features. The company is hiring software engineers for core product and AI development, technical support engineers for enterprise customers, data platform engineers for foundational systems, and security engineers for infrastructure and AI safety initiatives.
- Website
- notion.so
Likely interview questions
- Can you describe a time when you had to understand and optimize a system across multiple layers—from product code to infrastructure? What was your approach?
- Tell us about your experience building or working with event-based platforms. How have you handled scaling challenges as data volume increased?