Notion
Software Engineer, User Database Infrastructure
About this role
Notion is hiring a Software Engineer for User Database Infrastructure to build systems that make scalable, fast databases accessible to everyday knowledge workers. You'll lead the technical direction of a new database product from alpha to general availability, working across the stack (Postgres, Go, TypeScript, Node.js, React) while partnering with early customers to shape both architecture and product.
What you'll do
- Design and build systems to provision, manage, and scale customer Postgres instances
- Optimize query execution, indexing strategies, and data loading performance for growing workloads
- Develop safe schema evolution and migration systems for live databases
- Set architectural direction and roadmap for the database infrastructure product
- Partner with early customers to iterate on technical and product decisions
- Build observability and fleet operations automation to support multiple customers at scale
What they're looking for
- Production Postgres or MySQL experience with schema, indexing, and performance optimization
- Deep understanding of transactions, locking, concurrency, and data consistency
- Backend engineering with 10+ years of experience and technical leadership
- Full-stack development across Go, TypeScript, Node.js, and React
- Database architecture and infrastructure design
- API and systems design for developer-facing tools
- Customer collaboration and feedback iteration
- Problem-solving across product and infrastructure layers
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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
- Walk us through a time you optimized a slow database query or indexing strategy in production—what was the impact?
- How would you approach designing a schema migration system that allows users to evolve a live database safely without data loss?