Performance Engineer – Performance Analysis, Tuning

Supabase

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.

Posted 7/28/2026full-timeRemote • 🌎 Anywhere in the WorldMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates deep expertise in performance engineering and analysis of complex distributed systems, with a strong focus on turning insights into actionable improvements across product, infrastructure, and database teams. Proficient in performance methodologies and tooling, with a solid understanding of networking and cloud infrastructure performance.

Highest-signal resume keywords

Performance EngineeringComplex Distributed Systems AnalysisLinux Kernel InternalsNetworking and Cloud Infrastructure PerformanceStrong Written Communication

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Performance AnalysisQuery OptimizationIO SchedulingDatabase InternalsTCP Behavior Under LoadAWS Performance CharacteristicsVirtual Memory ManagementSchedulingNetworkingStorage Engine Management

Soft Skills

Problem CharacterizationPragmatic MindsetCollaboration

Tools & Technologies

MultigresOrioleDBPerformance MethodologiesObservability Tools

Industry Keywords

LatencyThroughputTail BehaviorCross-AZ LatencyNetwork Virtualization

Tech Stack

Tools & technologies

AWSCloudDistributed SystemsLinux

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

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.

Benefits

Comp & perks

Fully Remote
ESOP
Tech Allowance
Health Benefits
Annual Off-Sites
Flexible Work
Professional Development