What GraphQL Developers Actually Build
GraphQL serves as the API layer between frontend applications and backend services. Here's where your GraphQL developer will work:
API Layer Development
GraphQL developers design and implement the API that powers applications:
- Schema design - Defining types, queries, mutations, and subscriptions
- Resolver implementation - Writing the logic that fetches data for each field
- Performance optimization - Solving N+1 queries, implementing DataLoader patterns, caching strategies
- Authentication & authorization - Securing queries and mutations based on user permissions
Companies: GitHub (uses GraphQL for their API), Shopify (GraphQL Storefront API), Twitter (internal GraphQL APIs)
Full-Stack Applications
Many GraphQL developers work across the entire stack:
- Backend: Building GraphQL servers with Apollo Server, GraphQL Yoga, or Hasura
- Frontend: Consuming GraphQL APIs with Apollo Client, Relay, or urql
- Database integration - Connecting GraphQL resolvers to PostgreSQL, MongoDB, or other databases
Companies: Airbnb, Netflix, PayPal use GraphQL for internal APIs
Microservices & Federation
GraphQL Federation allows multiple services to contribute to a single GraphQL schema:
- Schema stitching - Combining multiple GraphQL APIs into one
- Service boundaries - Each microservice owns part of the schema
- Distributed data fetching - Resolvers call multiple backend services
Companies: Apollo Federation powers APIs at companies like Expedia, Major League Soccer
Real-Time Applications
GraphQL Subscriptions enable real-time data:
- Live updates - Chat applications, live dashboards, collaborative editing
- WebSocket connections - Maintaining persistent connections for subscriptions
- Event-driven architecture - Reacting to database changes, external events
The GraphQL Developer Skill Set
GraphQL requires a different mindset than REST. Here's what separates strong GraphQL developers:
Schema-First Development
GraphQL uses a strongly-typed schema that serves as the contract:
type User {
id: ID!
name: String!
email: String!
posts: [Post!]!
}
type Query {
user(id: ID!): User
users: [User!]!
}
Strong developers understand:
- Type system - Scalars, objects, unions, interfaces, enums
- Schema design patterns - Pagination, filtering, sorting conventions
- Versioning strategies - How to evolve schemas without breaking clients
Resolver Patterns & Performance
The resolver is where data fetching happens. This is where performance problems occur:
- N+1 queries - The classic GraphQL performance issue
- DataLoader pattern - Batching and caching database queries
- Resolver composition - Breaking complex resolvers into smaller functions
A junior developer writes resolvers that make a database call per field. A senior developer uses DataLoader to batch requests.
Client-Side GraphQL
Frontend GraphQL developers work with:
- Query optimization - Requesting only needed fields
- Caching strategies - Apollo Client cache normalization, Relay store
- Mutations & optimistic updates - Updating UI before server confirms
- Error handling - GraphQL error format, partial data handling
Skills Assessment by Use Case
If You're Building a Public API
- Priority skills: Schema design, versioning, rate limiting, documentation
- Interview signal: "How would you version a GraphQL API without breaking clients?"
- Red flag: No understanding of backward compatibility
If You're Building Internal APIs
- Priority skills: Performance optimization, federation, resolver patterns
- Interview signal: "How do you prevent N+1 queries in a complex query?"
- Red flag: Would make separate database calls for each field
If You're Building Real-Time Features
- Priority skills: Subscriptions, WebSocket management, event handling
- Interview signal: "How would you implement a live chat feature with GraphQL?"
- Red flag: Doesn't know the difference between queries and subscriptions
Common Hiring Mistakes
1. Confusing Query Writing with Schema Design
Writing GraphQL queries is easy. Designing schemas and optimizing resolvers is hard. Don't test candidates on query syntax—test them on schema design decisions and performance optimization.
2. Ignoring Performance Knowledge
GraphQL can be slow if not implemented correctly. N+1 queries, missing DataLoader patterns, and inefficient resolvers are common problems. Strong candidates should understand these issues and how to solve them.
3. Framework Obsession
Apollo is the most popular, but Relay, urql, and Hasura are also valid choices. A strong GraphQL developer understands the concepts and can adapt to different implementations. Don't require specific framework experience unless your codebase mandates it.
4. Not Understanding When GraphQL Isn't Right
GraphQL isn't always the answer. REST is simpler for CRUD operations. gRPC is better for microservices communication. Strong candidates can explain trade-offs and when to use GraphQL vs alternatives.
Recruiter's Cheat Sheet
Questions That Reveal Skill Level
| Question | Junior Answer | Senior Answer |
|---|---|---|
| "What's the difference between a query and a mutation?" | "Queries read, mutations write" | Explains caching implications, idempotency, when to use each |
| "How do you handle N+1 queries?" | "What's that?" | Discusses DataLoader, batching, field-level resolvers |
| "How would you version a GraphQL API?" | "Change the schema" | Explains deprecation, schema evolution, backward compatibility |
Resume Green Flags
- Mentions schema design or resolver optimization
- Experience with Apollo Federation or schema stitching
- Performance improvements ("Reduced API response time by 60%")
- Understanding of DataLoader or similar batching patterns
Resume Red Flags
- Only lists "GraphQL" without context (backend or frontend?)
- No mention of performance considerations
- Only tutorial projects (GitHub GraphQL API exploration)
- Can't explain when GraphQL isn't appropriate