Database Engineer
Ruby LabsAbout us
Ruby Labs is a leading tech company that creates and operates innovative consumer products. We offer a diverse range of opportunities across the health, education, and entertainment industries. Our innovative teams are driving the future of consumer-led products, and we're always looking for passionate individuals to join us. Learn more about our story at: https://rubylabs.com/about-us/
About the role
We are building a high-scale payment orchestration system that processes millions of financial transactions every month across multiple payment providers, regions, and products.
Our platform operates at the intersection of payments, billing, subscriptions, analytics, and internal CRM tooling, where data correctness, performance, and reliability are mission-critical. As our transaction volume and customer base continue to grow rapidly, our database layer has become one of the most important parts of the system.
We are looking for a strong Database Engineer who will own, scale, and evolve our data infrastructure, ensuring it remains fast, reliable, and ready for long-term growth.
You will be joining a high-talent, fully remote engineering organization with strong backend, infrastructure, and product teams. We value ownership, technical excellence, and pragmatic decision-making. Engineers at RubyLabs work on real scale, real money, and real impact.
As a Database Engineer at RubyLabs, you will be responsible for designing, operating, and optimizing databases in a high-volume payments environment. This role goes far beyond basic CRUD operations — you will work with large datasets, complex queries, performance bottlenecks, migrations on massive tables, and analytics pipelines.
You will collaborate closely with backend engineers and product teams to ensure our data layer supports both transactional workloads and analytical use cases, including internal CRM search and observability.
Key Responsibilities
Database Ownership & Scalability
Own and operate AWS Aurora (PostgreSQL) in a high-load production environment
Design and evolve schemas for large transactional domains (payments, customers, subscriptions, events)
Implement and maintain:
Table partitioning strategies (time-based, tenant-based, hybrid)
Advanced indexing (B-Tree, GIN, partial indexes)
Query optimization and execution-plan tuning
Handle databases with millions of new records per month while maintaining predictable performance
Performance Optimization
Analyze and optimize slow queries and production metrics
Identify and resolve:
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