Database Reliability Engineer, WorkOS

• You'll combine the mindset of a software engineer with deep database administration expertise to build automation, improve observability, and make our data layer self-healing wherever possible
• 5+ years of experience running PostgreSQL in production at scale, with strong knowledge of internals (WAL, MVCC, vacuum tuning, query planner, indexing, replication)
• Solid software engineering skills. You write production-quality code, not just scripts. Experience with Python, Go, Ruby, or similar languages
• Experience with infrastructure-as-code and configuration management (Terraform, Ansible, Chef, or similar)
• Strong SQL skills and the ability to review and optimize complex queries for high-throughput, low-latency environments
• Experience with database high-availability patterns: streaming replication, connection pooling (PgBouncer), failover automation (Patroni or similar)
• Familiarity with cloud database services on AWS (RDS, Aurora, DynamoDB, ElastiCache) or equivalent platforms
• Experience with monitoring and observability tools (Datadog, Prometheus, Grafana, or similar) applied to database workloads
• Comfort with on-call responsibilities and a track record of effective incident response
• Strong written and verbal communication skills. You document your work and share context proactively
• A proactive, ownership-driven mindset. When you see something broken, you fix it. When you see a pattern of toil, you automate it

Desirable

• The Infrastructure team ensures the WorkOS platform remains fast, reliable, and resilient at scale. We build the systems and practices that keep everything running smoothly—handling hundreds of millions of requests, minimizing downtime, and continuously improving service performance. Our team works across the stack and collaborates closely with product engineering teams
• As a Database Reliability Engineer on this team, you'll bring specialized database expertise to the Infrastructure organization. You'll own the full lifecycle of database management, from design and capacity planning through performance optimization and disaster recovery, ensuring data durability and scalability as WorkOS grows
• As a Database Reliability Engineer, you'll be the expert our engineering teams turn to for everything database-related. You'll work across the stack to ensure our PostgreSQL infrastructure (and related data stores) can support WorkOS's growth, from query optimization to capacity planning to incident response
• Own the reliability, performance, and scalability of WorkOS's PostgreSQL infrastructure
• Analyze and implement best practices for our database clusters, including replication, connection pooling, high availability, and disaster recovery
• Build and maintain observability for database metrics (query performance, replication lag, connection saturation, storage growth) and ensure we meet our database SLOs
• Provide database expertise to product engineering teams through migration reviews, query optimization guidance, and schema design consultation
• Develop automation and self-service tooling that enables engineers to safely interact with databases without bottlenecking on the DBRE team
• Participate in on-call rotations and lead incident response for database-related production issues, performing root cause analysis and implementing permanent fixes
• Plan and manage database capacity, forecasting growth and ensuring our infrastructure can handle increased workloads
• Collaborate with SREs to roll out infrastructure changes to production environments, with a focus on minimizing risk to the data layer
• Document operational procedures, runbooks, and architectural decisions so learnings become repeatable actions and eventually automation
• Drive improvements to backup and recovery strategies, regularly testing and validating disaster recovery procedures
• Projects You Could Work On
• Designing and implementing automated failover and self-healing for our PostgreSQL clusters
• Building a query performance analysis pipeline that surfaces slow queries and recommends index improvements before they become production issues
• Developing a database change management system that lets engineers safely run migrations with automated rollback capabilities
• Improving our disaster recovery posture by testing backup restoration, reducing recovery time objectives, and automating DR drills
• Creating capacity planning models that forecast database growth and trigger scaling actions proactively
• Building internal tooling and dashboards that give engineering teams visibility into their database usage patterns
• Optimizing our connection pooling and load balancing strategy across read replicas to improve throughput and reduce latency