Trusted by companies across the USA
A MongoDB engineer who fixes your slow queries, not a project quote
You hire one MongoDB developer who works inside your collections, your Atlas cluster, and your sprint cadence, billed hourly or monthly. They read your existing schema and aggregation code, find out why that one query takes nine seconds, and ship fixes without a long ramp.
Tell us what you need. We will match you within 48 hours.
Trusted by companies across the USA
Your developer shapes collections around how your app actually queries, deciding when to embed and when to reference instead of defaulting to one or the other. A user profile with a short, bounded list of addresses gets embedded; an order history that grows forever gets its own collection. The point is fewer round trips on the queries you run most.
Reporting, rollups, and analytics that would be a mess in application code get moved into aggregation pipelines that run close to the data. Your developer writes $match, $group, and $lookup stages in an order the query planner can actually use, then checks the explain output instead of guessing.
Most slow MongoDB queries trace back to a missing or wrong-order compound index, not the data size. Your developer reads the explain plan, adds the index the planner wants, and removes the ones that are only slowing writes. When a query still drags after that, they look at the document shape before reaching for a cache.
Your developer sets up the Atlas pieces that matter for your workload: the right tier, alerting on slow operations, and backups you have actually tested restoring. They use the Performance Advisor to catch index gaps before they show up as a support ticket.
When your stack runs on Node.js, your developer writes Mongoose schemas with validation and sensible defaults so bad data does not quietly land in a collection. They keep the model layer thin and predictable rather than burying business logic inside hooks.
They sit in your Slack, join your standup, and ask the product owner questions directly instead of guessing at intent. You are hiring a person who participates in the team, not a black box that returns finished tickets. When a data model decision is unclear, you hear about it the same day rather than after the wrong schema ships.
The engineer who learns your data model stays on it. We do not quietly rotate people in and out behind the scenes, because the context they build up around your collections is most of the value you are paying for.
Every commit and schema migration your developer writes belongs to you the moment it is pushed. There is no escrow, no licensing catch, and no claim on the work after the engagement ends.
Our team works from India, with a window that covers East Coast mornings and West Coast afternoons. You get live time for calls, pairing, and query review, plus progress overnight while your office is closed. An index change opened at your end of day is often tested and ready when you log back in.
We sign your NDA and a written agreement before your developer touches the cluster. Terms, ownership, and confidentiality are settled up front, not negotiated after the fact. That matters more than usual when someone is getting access to your production data.
If the developer is not the right match for your team, we swap them rather than make you live with it. You should not be stuck paying for a pairing that is not clicking.
You get a weekly view of what shipped through your own board and our written summaries over Slack and Loom. Nothing hides behind a 12-hour time difference.
One MongoDB developer working your full week, in your standups and your sprint plan. Best when the data work is steady and you want someone fully inside the team.
Half a developer's week, useful when you have ongoing schema and query work but not enough to fill a full schedule. The same person stays on it so context does not reset each sprint.
You draw on the developer's time as the work comes, tracked by the hour. This fits teams with a specific aggregation or performance problem to clear rather than a steady stream of tickets.
More than one developer when a single engineer cannot cover the surface area. We size and shape the group around the workload and your existing team.
Transparent pricing. No hidden fees.
From first contact to your developer writing code — here is how it works.
Get StartedWe start with a call about your data, your stack, and where the pain is. You walk us through your collections, your Atlas setup, and the queries that keep you up at night, so the match is grounded in your actual workload rather than a generic skills list.
We put forward a MongoDB developer whose experience lines up with your data problems, and you talk to them directly before anything is signed. If the first person is not right, you meet another; you are not handed someone and told to make it work.
In the first week the developer gets read access to the cluster, your repo, and your team channels, then maps your existing schema and index setup. They ask questions early instead of guessing, so the first changes respect how your data already flows rather than fighting it.
Your developer joins sprint planning and takes real tickets in their first cycle, not throwaway warm-up tasks. We keep that first sprint scoped to something measurable, often a slow query or a model change, so you can judge the fit on work that ships.
From there it is a steady cadence: daily presence in your channels, pull requests through the week, and a written recap of what landed. You always know what was worked on and what is next, with live overlap during US hours when you need to talk through a model decision.
Tell us about your data, your Atlas setup, and the queries that are slowing you down, and we will line up a MongoDB developer who fits how you already work.
Describe your project and requirements.