Staff Database Reliability Engineer, Stream

• Deep PostgreSQL expertise — you understand the internals (MVCC, vacuum and bloat, the query planner, indexing, replication) well enough to debug hard problems and reason from first principles, not from defaults
• Production ownership at scale — you've run Postgres behind high-traffic services with large datasets and high write throughput, and you've felt and fixed the failure modes that come with that
• Self-managed databases — you've operated Postgres yourself (on Kubernetes, bare-metal, or VMs), owning backup, replication, and high availability. Managed services alone aren't enough background for this role
• Sharding and scaling — you've sharded a real Postgres workload, not only table partitioning
• An engineering mindset — you can read and write code, and you connect database behaviour to application access patterns rather than treating the DB in isolation
• Judgement alongside AI tooling — we use AI heavily in our workflows; you should be able to use it well and know when it's wrong. Deep internals knowledge is what lets you tell the difference

Desirable

• We're looking for a hands-on Database Engineer to own PostgreSQL as a production system at Stream
• You'll work directly with a small, senior team and be responsible for the performance, reliability, and operability of the databases that store and serve data for Stream's entire real-time platform
• This is a deep, hands-on engineering role
• You'll spend your time in query plans, storage internals, and the operational realities of running databases under heavy, continuous load — not administering them from a distance
• Performance and internals — diagnose and resolve performance issues from the query down to the storage engine: indexing strategy, query planning, vacuum and bloat management, and tuning under sustained write load
• Reliability and operations — own the operational characteristics of our Postgres fleet, including backup, replication, and high availability as we take on more responsibility for running these systems ourselves
• Scaling the data layer — work on sharding, partitioning, and the architectural decisions that keep the database performant as data and traffic grow
• Beyond that, you'll set standards for how we run Postgres, collaborate closely with application engineers to connect database behaviour to real access patterns, and help shape the long-term direction of our data infrastructure