MongoDB and NoSQL development: data models, aggregations, scale

I design and develop backend systems on MongoDB and treat the data model as the foundation everything else rests on. Before writing the first query, I analyze data access patterns, decide what to embed in a document and what to reference, and shape collections so the most frequent reads come back in a single trip. It's thoughtful schema design that keeps a database fast as it grows, rather than silently degrading as data accumulates.

In day-to-day work I write and optimize aggregation pipelines, build indexes for your real queries and find slow operations that bog down the service. I read execution plans, eliminate full collection scans and choose indexes that help without bloating memory. When a single node isn't enough, I set up replicas for fault tolerance and shard large collections on a key that actually distributes load instead of creating hot spots.

I also build all the backend around the data: clean REST or internal APIs, safe migrations, backups that actually restore, and monitoring so you see problems before users do. Whether you're starting from scratch or rescuing an overgrown document store — I'll help you build it right.

— Schema design and data models for access patterns
— Aggregation pipelines and query optimization
— Indexes, sharding and replica sets
— Backend APIs, migrations and monitoring