Partner Engineer

Uber Uber · Consumer · London, United Kingdom · Engineering

Uber Partner Engineer focused on technical delivery of integrations with external restaurant tech partners, including POS, middleware, and ordering platforms. Responsibilities include scoping, designing, building, launching, and operating integrations, collaborating with partners on API implementation, building reusable integration patterns, and resolving production issues. Requires hands-on engineering experience with production integrations and proficiency in modern programming languages.

What you'd actually do

  1. Own technical delivery for a set of restaurant tech partners: scope, design, build, launch, and operate integrations end-to-end.
  2. Collaborate with partner engineers to implement Uber APIs/webhooks correctly and drive launch readiness (testing, rollback plans, monitoring).
  3. Build durable integration patterns (templates, libraries, runbooks) to reduce one-off work and accelerate future launches.
  4. Triage and resolve complex production issues across partner + Uber systems; improve observability and prevent repeat incidents.
  5. Partner tightly with the UK-based Restaurant Tech Partner Engineering Lead and cross-functional stakeholders across EMEA (Product/Platform/BD/Ops) to translate ecosystem needs into clear technical plans.

Skills

Required

  • Hands-on engineering experience shipping production integrations (APIs, webhooks/events, SDKs, distributed systems)
  • strong debugging/troubleshooting ability
  • Proficiency in at least one modern language (Python, Java, Go, Node.js)
  • ability to write and review production-quality code
  • Experience working directly with external technical stakeholders (partners/customers) to deliver implementations through ambiguity (technical scoping, timelines, launch readiness)

Nice to have

  • Experience with restaurant technology (POS, KDS/OMS, menu/catalog sync, payment flows, delivery aggregation/middleware) or adjacent commerce ecosystems.
  • Strong systems instincts around reliability, observability, and scale (idempotency, retries, rate limits, monitoring, incident response).
  • Data fluency: SQL + analytics to diagnose integration health and drive prioritization (failure taxonomy, SLA/SLO thinking).
  • Track record building reusable integration assets (reference implementations, test harnesses, partner onboarding docs, automation/tooling).