Performance Engineer – Performance Analysis, Tuning

Job not on LinkedIn

🕒 July 28

🌏 Anywhere in the World

⏰ Full Time

🟡 Mid-level

🟠 Senior

👷🏻‍♀️ Engineer

👻 Ghost score 30%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Supabase

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2020

☁️ SaaS

🔌 API

🤖 Artificial Intelligence

💰 $80M Series B on 2022-05

SaaS • API • Artificial Intelligence

Supabase is an open source alternative to Firebase, providing a range of backend tools designed to help developers start and scale their applications effectively. It offers features such as a full Postgres database, authentication with Row Level Security, instant APIs, Edge Functions for custom code, real-time data synchronization, and storage for large files. Developers can integrate machine learning models, utilize RESTful APIs, and take advantage of platform-integrated best of breed products. Supabase is designed to be highly portable, extendable, and user-friendly, making it a powerful choice for startups and enterprises looking to innovate quickly and efficiently.

📋 Description

• 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

• 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

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