Hire a TanStack Query developer when your React app feels slow or inconsistent because server data is handled by hand: fetches inside effects, results copied into a global store, the same request sent five times, lists that go stale after a save. We place engineers who fix the data layer and leave your team with conventions it can keep. For a whole project instead of a person, see our React development services.
What do we vet for in a TanStack Query developer?
Using useQuery is easy. Using it well is a different skill. These are the traps we test for:
- Query keys. Keys that miss a variable return the wrong cached data. We ask candidates to design keys for a filtered, paginated list and explain what invalidating a prefix does.
- Stale time and gc time. The default stale time is zero, so a query refetches on every mount and window focus until someone sets it on purpose. In version 5
cacheTimeis nowgcTime, and engineers who learned v3 often mix the two up. - Loading flags. In v5
isPendingmeans no data yet andisLoadingmeans pending and fetching. A wrong flag shows spinners on every refetch or hides the first load. - Mutations and invalidation. We check for optimistic updates with rollback, and for invalidating the right keys instead of refetching everything.
- Server state in a client store. Copying query data into Redux or Zustand creates two sources of truth. A good candidate says when that is justified, which is rare.
- SSR and hydration. In Next.js, data prefetched on the server must be dehydrated and a client created per request, or users see mismatches and leaked cache between requests.
- Error handling.
throwOnErrorand error boundaries, retry rules per error type, and what the user sees when a request fails twice.
We also review real code from an app where the candidate set up caching.
What do the first weeks look like?
The first days go to reading. The engineer maps every fetch in the app, lists duplicate and unkeyed requests and agrees naming conventions for keys with your team. After that the work is concrete:
- Wrap the API calls behind query option factories, so keys and fetchers live in one place.
- Migrate the three or four screens with the worst symptoms, such as stale lists or double fetching.
- Add mutation helpers with invalidation rules and optimistic updates where users notice latency.
- Set cache times per data type and write them down.
- Add tests around query keys and error states.
If you are on Next.js, the same engineer can set up server prefetching and hydration. Our Next.js developers cover rendering strategy if you need that as well.
Which engagement model fits?
| Model | Fits when | How it works |
|---|---|---|
| Dedicated developer | One app, a clear backlog, a team that can review code | The engineer joins your standups and repository. See IT staff augmentation. |
| Team extension | Several apps or a shared API client | A small group works on data layer, design system and tests together. See hire a dedicated team. |
| Project | You want an outcome, not hours | We audit, fix and hand over with documentation for a scoped price. |
Hourly work falls in the band of $50 to $150 per hour, depending on seniority and scope. We start after a short intro call, where you describe the app, the stack and the role, and you interview the engineer before any work begins.
When is TanStack Query not the answer?
If your app has almost no server data, or all state is local UI state, you do not need it. If you use GraphQL with a normalized cache already, Apollo or urql may cover the same ground. And if the real problem is a slow API, caching in the browser only hides it. We say so in the intro call. Parent hub: hire React developers.
