Partner Engineer

About the Role
Uber’s delivery ecosystem is powered by deep technical integrations with an ever-growing network of external partners. As a Portfolio Partner Engineer, you’ll be embedded in the restaurant tech ecosystem—working with POS, middleware, ordering, and operational platforms—to help partners build on Uber’s platform and scale reliably. You’ll operate in an “embedded” model: equal parts architecture + hands-on execution, with outsized impact on integration speed, quality, and day-2 reliability.
What the Candidate Will Need / Bonus Points
---- What the Candidate Will Do ----
Own technical delivery for a set of restaurant tech partners: scope, design, build, launch, and operate integrations end-to-end.
Collaborate with partner engineers to implement Uber APIs/webhooks correctly and drive launch readiness (testing, rollback plans, monitoring).
Build durable integration patterns (templates, libraries, runbooks) to reduce one-off work and accelerate future launches.
Triage and resolve complex production issues across partner + Uber systems; improve observability and prevent repeat incidents.
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.
---- Basic Qualifications ----
Hands-on engineering experience shipping production integrations (APIs, webhooks/events, SDKs, distributed systems) and strong debugging/troubleshooting ability.
Proficiency in at least one modern language (Python, Java, Go, Node.js) with the 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).
---- Preferred Qualifications ----
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).
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