Senior Staff Engineer - Shipping

Shipping is one of the most important aspects of an ecommerce business, whether it’s domestic or international shipping. It can also be one of the most challenging things to get right. Our mission is to help merchants succeed by providing shipping solutions that power all entrepreneurs. Our scope spans from shipping strategies, rates, and calculating estimated delivery dates at checkout, to carrier integrations, shipping label management and workflows, and tracking shipments.
Key Responsibilities:
- Own technical strategy across a multi-team Shipping domain (labels, carrier integrations, tracking, delivery predictions).
- Lead architecture and execution for the Shipping Partner Platform to expand global shipping label coverage.
- Lead architecture and execution for shipping workflows across Admin, Core, and our shipping services monolith (Shipify).
- Build and evolve the Package Tracking streaming pipeline (Flink) to produce higher quality tracking updates.
- Develop models and a state machine to parse raw tracking data and predict:
- Estimated delivery dates.
- Package location and state.
- Suggested actions.
- Build shipping fraud detection models and supporting systems.
- Build scalable data pipelines (with Query Engine) to ensure feature data is available and reliable for modeling.
- Improve reliability, performance, and operability (production excellence, incident learnings, on-call health).
- Simplify legacy surfaces and reduce operational drag via better patterns, tooling, and paved paths.
- Mentor Staff and Lead developers and help grow new technical leaders across the org.
- Collaborate with senior leaders to drive alignment and optimize for global maxima.
Qualifications:
- Proven ability to lead across teams and systems, especially in ambiguous problem spaces.
- Strong architecture and execution skills in complex domains with multiple integrations and workflows.
- Strong experience with streaming and data processing systems (Flink preferred).
- Experience building scalable data pipelines and ensuring high-quality feature data for downstream consumers.
- Strong production engineering fundamentals: reliability, observability, incident response, and performance.
- Strong communication skills and ability to set direction, influence, and mentor across an org.
Nice to have:
- Experience with shipping or logistics domains (carrier integrations, labeling, tracking, delivery predictions).
- Experience with fraud detection systems and modeling.
- Experience designing state machines for event-driven systems and noisy external data sources.
- Experience operating systems at very large scale (high event volume, high reliability requirements).