Sr. Engineer, Database Reliability

Zapier•San Francisco, CA

5d•$174,200 - $261,200•Remote

About The Position

Zapier is seeking a Database Reliability Engineer (DBRE) to join the State team, which owns the platform behind Zapier’s stateful services: its MySQL and PostgreSQL relational database fleet, Redis and ElastiCache caching layer, and tooling that helps product teams use these systems safely and reliably. This is the most senior DBRE role on the team and will serve as the technical center of gravity for database and cache work, setting operational standards and helping grow the DBRE practice. The role sets direction for data infrastructure and tackles complex operational challenges. It shapes automation, observability, performance, reliability, and disaster-recovery practices, while making the recommended approach easy for product teams to adopt. The engineer partners with internal customers on workload needs, design decisions, query and schema patterns, and capacity planning; participates in production on-call; and builds documentation, tooling, templates, and runbooks that help teams work effectively and independently. The position also leads design reviews and mentors engineers, raises the operational bar for the data layer, and applies AI tools thoughtfully to automation, query and log analysis, documentation, and incident investigation. Zapier is an all-remote company, though employees must work from countries where Zapier can employ them.

Requirements

At least 7 years of experience in systems administration, systems engineering, or software development.
At least 4 years of experience running production relational databases.
Deep expertise in MySQL or PostgreSQL and working knowledge of the other, including their ecosystems of extensions and tools.
Working knowledge of caching systems such as Redis, including designing and operating them at scale and understanding tradeoffs with the underlying database.
Experience designing and maintaining highly available, cloud-based database systems in AWS or another cloud platform.
Experience managing infrastructure with Terraform or similar infrastructure-as-code tooling.
Comfort operating stateful services alongside Kubernetes or other distributed systems, and understanding the tradeoffs of running data workloads in and around orchestrated environments.
Experience implementing metrics, logging, and alerting for data systems with tools such as Datadog, Prometheus, or CloudWatch.
Ability to use query performance data, replication lag, and cache hit rates as operational signals.
Ability to partner with product teams, understand workloads, explain tradeoffs, and provide thoughtful support.
Experience participating in an on-call rotation for production data systems.
Strong documentation skills, including documenting knowledge for asynchronous use.
Ability to review designs, mentor engineers, and help raise team practices.
Ability to write code to automate work and solve systems problems, including working with application code or backend services as needed.
Experience using AI tools in technical work, with sound judgment about their reliability and risks, especially in production data systems.

Responsibilities

Own reliability of the caching layer, including capacity planning, failover behavior, upgrade strategy, and healthy usage patterns for Redis Enterprise and AWS ElastiCache.
Participate in the production on-call rotation and serve as an escalation point for data-layer issues during incidents.
Support internal customers with data-layer troubleshooting and advice, and turn recurring questions into documentation and tooling.
Manage database and cache infrastructure as code by evolving Terraform modules and provisioning workflows so changes are repeatable, reviewable, and safe.
Build database and cache standards and templates in the internal platform’s golden path to enable scalable, performant, and secure setups.
Build and maintain data-layer observability, including dashboards, alerts, and SLOs for database and cache health.
Identify and implement strategies to improve performance and resilience across MySQL, PostgreSQL, and Redis fleets.
Work with development teams on architecture decisions for new services and technologies, including database engine selection and caching design.
Advise product teams on schema design, query patterns, and capacity planning.
Lead design reviews for data-layer work and mentor engineers on database and cache practices.
Turn experience into documentation, patterns, and runbooks that improve how the team operates the data layer.
Automate repetitive work and build tools to improve team effectiveness; investigate application code and build backend services when needed to solve systems problems.
Use AI tools for automation code, query-plan and log analysis, runbook drafting, and incident investigation, applying judgment about the reliability and risks of AI output.