[All remote jobs](https://jobicy.com/jobs.md)[![Supabase logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2026/06/611d3bfa-221.png)](https://jobicy.com/company/supabase.md)[Supabase](https://jobicy.com/company/supabase.md) # Performance Engineer – Performance Analysis & Tuning Review the role, location requirements, compensation details, and application process before deciding whether this opportunity fits your next career move. [Apply for this job](#job-application)[View company](https://jobicy.com/company/supabase.md)ShareRemote from🌐 AnywhereSalaryUndisclosedDepartment[Software Engineering](https://jobicy.com/categories/engineering.md)EmploymentFull TimeExperienceOpen levelPublished23 Oct 2026Apply before22 Nov 2026Listing views27Application actions2Application toolkit ## Make your next move. Prepare your resume, explore your fit, and draft a cover letter for this opportunity. AI Summary ## The role, at a glance. Supabase is seeking a senior performance engineer to identify, characterize, and resolve bottlenecks across its distributed database platform, APIs, networking, and cloud infrastructure. The role spans the full stack, from query optimization and database storage engines through Linux kernel behavior, I/O scheduling, and AWS network paths. This engineer will build repeatable analysis methods and tooling, partner with database, infrastructure, and observability teams, and drive measurable production improvements. It is an early position on a new performance team, with substantial influence over engineering practices and performance priorities. The company operates as a globally distributed, fully remote organization. ## Role DNA A quick view of the complexity, pace, ownership and collaboration implied by the job description. ### Job Complexity 5/5EasyHard ### Pace & Pressure 4/5RelaxedFast-paced ### Autonomy Level 5/5GuidedFull ownership ### Communication Load 5/5IndependentCollaborative AI insightThis is a highly specialized systems-performance role requiring deep expertise across databases, Linux internals, cloud infrastructure, networking, profiling, and distributed systems. Success also depends on independently converting technical findings into prioritized fixes across multiple engineering teams. ## Salary analysis Estimated compensation compared with the broader US market for similar roles. Estimated job median (per year)Market rate$190,000US market range (per year)$160k–$230k0$253.00k AI insightThe yearly pay period is inferred from the job context; it was not explicitly stated by the employer. No employer salary was disclosed. Estimated annual USD compensation for a senior distributed-systems performance engineer in the US market is approximately $160,000–$230,000, with an estimated midpoint of $190,000 per year; this is an AI market estimate rather than employer-provided compensation. ## Core skills Skills and capabilities most closely associated with this opportunity. [Performance engineering](https://jobicy.com/jobs?search_keywords=Performance%20engineering.md)[Distributed systems](https://jobicy.com/jobs?search_keywords=Distributed%20systems.md)[Linux kernel internals](https://jobicy.com/jobs?search_keywords=Linux%20kernel%20internals.md)[Database performance tuning](https://jobicy.com/jobs?search_keywords=Database%20performance%20tuning.md)[PostgreSQL](https://jobicy.com/jobs?search_keywords=PostgreSQL.md)[Query optimization](https://jobicy.com/jobs?search_keywords=Query%20optimization.md)[Systems profiling](https://jobicy.com/jobs?search_keywords=Systems%20profiling.md)[Performance tracing](https://jobicy.com/jobs?search_keywords=Performance%20tracing.md)[Network performance](https://jobicy.com/jobs?search_keywords=Network%20performance.md)[TCP tuning](https://jobicy.com/jobs?search_keywords=TCP%20tuning.md)[AWS infrastructure](https://jobicy.com/jobs?search_keywords=AWS%20infrastructure.md)[I/O optimization](https://jobicy.com/jobs?search_keywords=IO%20optimization.md)[Observability](https://jobicy.com/jobs?search_keywords=Observability.md)[Latency analysis](https://jobicy.com/jobs?search_keywords=Latency%20analysis.md)[Capacity scalability](https://jobicy.com/jobs?search_keywords=Capacity%20scalability.md) Sample interview questionsHow would you investigate an intermittent tail-latency spike affecting a database-backed API?I would first establish the scope, affected endpoints, timing, and percentile behavior using production metrics and traces. I would correlate application spans with database execution, connection-pool behavior, host CPU and memory pressure, storage latency, network retransmissions, and scheduler activity. I would then reproduce or safely characterize the condition, isolate the dominant contributor, and provide the owning team with evidence, expected impact, and a validation plan. What signals would you use to distinguish a database query-planning problem from a storage or kernel I/O problem? For query planning, I would examine execution plans, row estimates, join choices, lock waits, buffer behavior, and query-level CPU time. For storage or kernel I/O issues, I would correlate database waits with device latency, queue depth, page faults, writeback activity, filesystem activity, and I/O scheduler metrics. The distinction comes from tracing where elapsed time accumulates and validating the hypothesis through controlled workload or configuration changes. Describe a methodology for assessing cross-availability-zone network latency in a cloud workload. I would measure baseline round-trip time, connection establishment, throughput, retransmissions, and tail latency between relevant nodes and availability zones under representative load. I would compare these results with application traces to determine whether network delay materially affects request paths, replication, or pooler hops. Based on findings, I would evaluate placement, traffic routing, batching, connection reuse, and architecture changes while measuring the resulting trade-offs. How would you help engineering teams adopt performance analysis practices rather than relying on a central performance team? I would create lightweight, repeatable workflows for baselining, profiling, regression testing, and interpreting key service-level metrics. Tooling should make useful traces, dashboards, and comparison reports easy to access, while written guidance should explain how to form and validate performance hypotheses. I would also partner on early investigations so teams gain confidence applying the methodology independently. How do you prioritize competing performance improvements across a large platform? I prioritize using measured user impact, affected workload volume, severity of tail behavior, scalability risk, implementation cost, and confidence in the proposed fix. I communicate the evidence in a concise problem statement that identifies the bottleneck, likely cause, expected benefit, and validation criteria. This makes prioritization transparent and helps teams commit to improvements with the highest demonstrated return. Opportunity details ## About this role. ### About Supabase Supabase is the Postgres development platform, built by developers for developers. We provide a complete backend solution including Database, Auth, Storage, Edge Functions, Realtime, and Vector Search. All services are deeply integrated and designed for growth. ### About the Role We’re hiring experienced performance engineers to find and land performance wins across the Supabase stack — from the query optimiser to block device level, and across the network paths and cloud infrastructure that connect our distributed platform. This is a performance delivery role: real, measured improvements to our database, platform, and APIs as we scale toward enterprise and platform-grade workloads. The methodologies you develop and tooling you build exist to multiply that delivery. You’d join a new performance team as one of its first members, working alongside a deeply seasoned performance engineer, with the team growing to roughly six this year. There’s no legacy process to inherit — you’ll help define how performance engineering works at Supabase. ### What you’ll do * 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. ### Problems you might work on * Tune the kernel’s paging behavior to production workloads * Reduce memory overhead in OrioleDB and Multigres * Identify and eliminate sources of latency spikes from application to kernel level * Identify scalability bottlenecks across the entire stack and work the appropriate teams in Supabase and the wider community to resolve them ### What we’re looking for * 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. ### What We Offer * Fully Remote We hire globally. We believe you can do your best work from anywhere. There are no Supabase offices, but we provide a WeWork membership or co-working allowance you can use anywhere in the world. * ESOP Every team member receives ESOP (equity ownership) in the company. We want everyone to share in the upside of what we’re building together. * Tech Allowance Use this budget to set up your ideal work environment—laptop, monitor, headphones, or whatever helps you do your best work. * Health Benefits Supabase covers 100% of health insurance for employees and 80% for dependents, wherever you are. Your wellbeing and your family’s health are important to us. * Annual Off-Sites Once a year, the entire company gathers in a new city for a week of connection, collaboration, and fun. It’s a highlight of our year. * Flexible Work We operate asynchronously and trust you to manage your own time. You know what needs to be done and when. * Professional Development Every team member receives an annual education allowance to spend on learning—courses, books, conferences, or anything that supports your growth. ### About the Team Supabase was born-remote and open-source-first. We believe our globally distributed team is our secret weapon in building tools developers love. * ~400 team members * 60+ countries * 20+ languages spoken * Over $1B raised (including our $500M Series F) * 540,000+ community members We move fast, build in public, and use what we ship. If it’s in your project, we probably use it in ours too. We believe deeply in the open-source ecosystem and strive to support—not replace—existing tools and communities. Show more [Apply now >](https://jobicy.com/jobs/156581-performance-engineer-performance-analysis-tuning.md) > Annual salary information is not provided for this position. 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