Hire talent · Back end
Hire MongoDB developers who stay after the database goes live.
Senior engineers who join your repo, your sprint and your standups. They design the data model, write the aggregation pipelines and tune the slow queries, then stay to run what they built rather than handing it over and leaving.
What they do
Hire MongoDB developers who stay after the database goes live, end to end.
Document schema design
We model your documents around how the application actually reads and writes, deciding what to embed and what to reference. Get this wrong and every query after it is a workaround.
Aggregation pipelines
Reporting, roll-ups and lookups written as aggregation stages rather than pulled into application code. We keep pipelines readable, tested against real data volumes, and documented so your team can change them.
Indexing and query performance
We read the slow query logs, check the execution plans and add compound indexes that match your query shapes. Then we remove the indexes nothing uses, because each one costs you on every write.
Atlas setup and operations
Cluster sizing, replica sets, automated backups, alerting and restore drills, on MongoDB Atlas or a self-hosted deployment. A backup you have never restored from is not a backup.
Migrations and version upgrades
Moving off a relational database, splitting a collection or stepping through major MongoDB versions, run as staged migrations with a rollback path and no unplanned downtime.
Application and AI integration
Wiring MongoDB into Node, TypeScript and Python services through the official drivers, and into retrieval for AI agents and copilots using Atlas Vector Search where it fits.
How it runs
Plan. Build. Run.
A 30 minute call
We ask what you are building, what your data looks like now and where it hurts. You leave knowing whether MongoDB is the right store for it, even if the answer is that it is not.
Scope, timeline and price
You get a fixed scope with a named engineer, a start date and a price before any work begins. If the work is too vague to scope honestly, we say so and propose a short paid discovery first.
Embed and build
Your engineer joins your repo, your ticket tracker and your standups. Work goes through your review process, with schema changes and index additions written down as they land.
Run it after launch
When it is live you can keep the engineer, move to our managed retainer, or take it fully in house with the documentation and handover to do that properly.
Why infoloop
We do not hand over and leave.
- We stay after launchMost engagements end at handover. Ours can carry on as a managed retainer: monitoring, fixes against agreed response targets, security updates and a monthly report on what changed.
- Senior engineers, matched to the workYou meet the person before anything starts and you keep the same person throughout. No bench rotation, no CV pile to sift through, no juniors billed as seniors.
- Fixed scope and a fixed priceBefore we start you get a written scope, a timeline and a number. Changes are agreed and priced separately rather than quietly absorbed into an open-ended hourly bill.
- Your code, your cluster, your accessEverything lives in your repository and your MongoDB account from day one. Credentials stay yours. Nothing we build depends on us keeping a login.
- Built to be handed overSchema decisions, index rationale and migration steps are documented while the work happens. Your in-house team can pick it up whenever you want them to.
What you get
Every engagement includes these, in writing, before work starts.
- A documented data model covering every collection, field and relationship
- Index definitions with the query each one exists to serve
- Aggregation pipelines committed to your repository, not pasted into a console
- Migration scripts with a tested rollback path for each step
- Backup, restore and alerting configured in your own MongoDB account
- A handover pack your in-house engineers can work from without us
Who this is for
Three situations where this is the right call.
Your queries got slow as the data grew
The app was fine at ten thousand documents and is painful at ten million. You need someone to read the execution plans, fix the indexes and reshape the collections causing it, without stopping the roadmap for a rewrite.
You are moving off a relational database
The relational schema no longer matches how the product works, and nobody on the team has modelled documents before. You want someone who has, working alongside them, rather than a consultant who hands over a diagram and leaves.
You need MongoDB depth your team lacks
Your engineers are strong but nobody owns the database. You want one senior person embedded for a defined stretch to set the patterns, unblock the work and leave the team able to carry on without them.
Questions
What buyers ask us first.
What does it cost to hire a MongoDB developer through infoloop?
Can your engineer work in our existing repository and process?
Do you work with MongoDB Atlas or self-hosted deployments?
What happens after the database work is live?
How do we know the engineer is right before we commit?
Is MongoDB the right database for what we are building?
Tell us what your data is doing. We'll bring the engineer.
One 30 minute call to look at your collections, your queries and what is hurting. You leave with a scope, a timeline and a price, and an honest view on whether MongoDB is the right tool for the job.