Data architecture built to last.
High-availability relational and NoSQL databases designed for complex relationships, massive throughput, and enterprise-grade reliability.
PRIMARY
NOSQL
What I build
at the data layer.
Schema Design
Normalized relational schemas with proper indexing, constraints, and migration strategies for evolving data models.
Query Optimization
Slow query analysis, index tuning, connection pooling, and read replicas for sub-millisecond response times.
Backup & Recovery
Automated backups, point-in-time recovery, multi-AZ replication, and disaster recovery planning.
Data Modeling
Entity-relationship design, denormalization strategies, and hybrid SQL/NoSQL architectures for complex domains.
ETL & Migrations
Zero-downtime schema migrations, data transformation pipelines, and legacy database modernization.
Security & Compliance
Row-level security, encryption at rest, audit logging, and GDPR/CCPA-compliant data handling.
Technical ecosystem.
PostgreSQL · MySQL · AWS RDS · Supabase
MongoDB · DynamoDB · Redis · Elasticsearch
Prisma · Mongoose · Drizzle ORM · TypeORM
pgAdmin · MongoDB Compass · DataGrip · AWS CloudWatch
Data done right.
Schema-First Development
I design the data model before writing a single line of application code. Good data architecture prevents 80% of future problems.
Performance Engineering
EXPLAIN ANALYZE isn't optional — it's part of every query I write. Indexes, partitioning, and connection pooling are standard.
Migration Safety
Zero-downtime migrations with rollback plans. Your production database is treated with the respect it deserves.
Right Tool for the Job
Postgres for relationships, MongoDB for flexibility, Redis for speed. I choose based on your data patterns, not trends.
Need a database
that performs?
I design data architectures that are fast, reliable, and maintainable. No premature optimization, no over-engineering.