About the role

Join Supabase as a Performance Engineer to enhance platform performance and optimize systems. Collaborate with database and infra teams to deliver measurable improvements across the stack.

Responsibilities

Find bottlenecks in live production systems and characterize them precisely enough that the owning team can act on them without you in the room.
Partner closely with database teams (e.g. Multigres, OrioleDB) and infra teams to land concrete performance improvements.
Build, communicate, and evolve performance methodologies and tooling that turn live production data into actionable insight.
Partner with the observability team to capture the right signals and establish a unified view of platform performance (latency, throughput, tail behavior) across products.
Help teams self-serve performance analysis and make performance a first-class engineering concern.

Deep experience in performance engineering, specifically performance analysis of complex distributed systems.
You can walk the whole stack: follow a tail-latency problem from the query optimizer through the syscall boundary to the IO scheduler — or across pooler hops, network paths, and availability zones — reading profiles and traces at every layer.
Depth on at least one end of that stack: Linux kernel internals (virtual memory, scheduling, networking, IO) or database internals (query planning, storage engines, buffer and WAL management)
Strong working knowledge of networking and cloud infrastructure performance: TCP behavior under load, network virtualization overhead, and the performance characteristics of AWS primitives (EBS throughput and IOPS, instance network limits, placement groups, cross-AZ latency).
Proven ability to turn performance insights into real product and architecture improvements — including getting teams you don't belong to to prioritize and ship the fix.
Strong written communication: your problem characterisations are precise, reproducible, and compelling on their own.
Pragmatic, tooling-oriented mindset; comfort working across product, infra, and database teams.