Data & AI
Hire MongoDB engineers who design schemas that scale.
Document modeling, aggregation pipelines, Atlas, sharding — our nearshore MongoDB squads ship databases ready for growth.
Why it matters
Why MongoDB still wins for the right workloads
MongoDB has matured into a serious document database with transactions, joins, aggregation, vector search, and Atlas as a managed offering. It thrives where your data shape changes faster than your sprints — content platforms, IoT, catalogs, user-generated content. The hard part: schema design in MongoDB is harder than in SQL, not easier, and most engineers learn that lesson the painful way.
Where MongoDB earns its keep
Content and catalog platforms with evolving data shapes
IoT and event ingestion at high write volume
User-generated content with flexible nested structures
Multi-tenant SaaS with per-tenant schema variation
Why outsource
How outsourcing accelerates your MongoDB roadmap
MongoDB rewards experienced data modelers — exactly the engineers hardest to hire fast.
Schema design that doesn't haunt you
Embedding vs referencing, denormalization strategy, growth-aware modeling from day one.
Aggregation pipeline mastery
Complex queries built right — indexed, staged, profiled, observable.
Atlas-native operations
Sharding, replica sets, backups, alerts, performance advisor — the cluster runs itself.
Migration into and out of MongoDB
Postgres to Mongo, polyglot persistence, change-data-capture pipelines.
What we ship
What our MongoDB squads deliver
MongoDB is unforgiving with bad schema choices. Our engineers ship the kind that survives 10x growth.
Production schema design
Modeling reviews, index strategy, growth simulations.
Atlas operations
Sharding, replica configuration, backup and DR strategy.
Aggregation and search
Atlas Search, Vector Search, complex pipelines, performance tuning.
Hire MongoDB engineers in 48 hours.
Greenfield schema design, performance rescue, Atlas migration — our squads have shipped it.