Software Engineer (User Database Infrastructure)

Notion; United States; On-site; USD 180,000 - 260,000; Full time

Job summary

Notion is seeking a backend‑leaning engineering leader to steer the architecture and roadmap as we advance a new product from alpha to GA. You will collaborate with early customers to understand workloads and translate feedback into scalable, reliable systems.

With 10+ years building and operating production software, you will drive performance, concurrency, and data correctness across Postgres, Go, TypeScript, Node.js, and React, while mentoring teams and delivering practical outcomes.

Qualifications

• 10+ years of experience building and operating production software.
• Production relational database experience (Postgres/MySQL).
• Deep Postgres expertise and high-concurrency workloads.
• Strong backend engineering fundamentals; able to lead cross-team initiatives.
• Fluency with AI-assisted engineering.
• Willingness to work across the stack.

Responsibilities

• Build backend systems and data infrastructure to support scaling.
• Lead architectural direction and product roadmap with early customers.
• Collaborate with teammates and customers to shape solutions.
• Improve query execution, indexing, and data loading for large datasets.
• Provide technical guidance through design reviews and mentorship.

Skills

Backend engineering

Technical leadership

PostgreSQL expertise

Performance tuning

Concurrency control

Query optimization

AI-assisted development

Cross-team collaboration

System design

Tools

PostgreSQL

Go

TypeScript

Node.js

React

Job description

• You’ll build the systems that let any knowledge worker leverage fast, scalable databases without having to become a DBA
• You’ll be a hands-on technical leader, helping set the architectural direction and roadmap as we take a new product from early alpha to general availability
• You’ll work directly with early customers to shape foundational technical and product decisions
• Then, together, we’ll work on scaling as adoption and workloads grow
• This is a backend-leaning role with work spanning the stack
• You might build the systems that provision and manage a fleet of customer Postgres instances, design how user-defined schemas evolve safely, or make complex queries execute efficiently
• You’ll also follow those systems into the product: improving how a table loads, how users understand a slow operation, or how an agent safely works with their data
• You’ll help shape the architecture and the product together
• Some problems call for a better abstraction, others for a better default, and others for rethinking what we ask the user to do in the first place
• You’ll work with teammates and customers to find those answers, ship practical solutions, and evolve them as usage grows
• Our stack includes Postgres, Go, TypeScript, Node.js, and React
• Take a new product from alpha to general availability. Work with early customers to understand what matters, iterate on feedback, and help shape what we ship
• Make real customer workloads fast. Improve query execution, indexing, and client data loading so performance holds up as datasets grow and workflows become more demanding
• Build systems businesses can trust with their data. Make schema changes, concurrent writes, permissions, and recovery reliable enough for customers to build essential workflows on top
• Make powerful capabilities approachable. Turn database provisioning, migrations, and indexes into a reliable, easy-to-use product experience that gives people the power of a database without the burden of managing one
• Build for the customers who come next. Automate database provisioning and fleet operations, strengthen observability, and evolve the architecture so we can serve many, many customers

A systematic approach to performance. You use query plans, traces, profiles, and experiments to find bottlenecks and verify improvements. You’re willing to follow a problem across storage, services, and client code rather than stopping at a team boundaryProduct judgment. You’re interested in who will use what you build, not just how it works. You can turn a customer’s problem into a technical approach and recognize when a better default or simpler workflow would solve it more effectivelyProduction relational database experience (e.g., Postgres or MySQL). You’ve made decisions about schemas and indexes, analyzed database performance, and debugged issues involving transactions, locking, or concurrency. Your experience goes beyond accessing a database through an ORMEngineering experience and technical leadership. You bring 10+ years of experience building and operating production software, with a track record of setting technical direction and leading complex, cross-team initiatives from concept through delivery. You identify the most important problems to solve, turn ambiguous goals into a technical strategy, and align engineers and partner teams around a practical plan. You stay hands‑on while helping others make better decisions through design reviews, mentorship, and clear technical guidanceFluency with AI-assisted engineering. You use AI to accelerate exploration, implementation, and testing while taking responsibility for understanding and validating the resultStrong backend engineering fundamentals. You’ve built services that need to remain correct under concurrency and failure. You can reason about retries, partial failures, consistency, and the trade‑offs involved in reliable reads and writesWillingness to work across the stack. You bring backend depth, but you’re comfortable learning unfamiliar systems and working in client code when that’s what delivering a good experience requiresIf you’re excited about this role but don’t meet every bullet, we still encourage you to applyExperience building query layers, sync engines, change‑data‑capture pipelines, permission systems, or other reusable data abstractionsExperience managing fleets of databases or building database platforms, including provisioning, upgrades, backups, and recoveryDeep Postgres expertise, such as advanced query optimization, performance tuning, or workload isolation for large datasets and high‑concurrency workloads