ironquill.tech/board

$ cat jobs/performance-engineer-performance-analysis-tuning-supabase-fc2037262196.json

Performance Engineer - Performance Analysis & Tuning

Supabase·Worldwide·Remote·mid
postgres
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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 bottl

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