Software Engineer III, Data Product

Shippo

11d•Remote

About The Position

The Data Products team is responsible for building and maintaining the core data products that power Shippo’s customer-facing features. This includes business rules automation, ML-based recommendations, analytics, and configuration systems. As a Software Engineer III on this team, you will contribute across the full spectrum of our work, partnering with data science and ML teams to bring model outputs into reliable, well-instrumented production services. You will design systems with auditability in mind, considering versioning, immutable event logs, and traceable decision-making. You will evaluate and implement data product patterns appropriate to the problem, whether that’s a condition evaluation engine, a scoring API, or a configurable workflow. You will also contribute to team-level quarterly goals, owning end-to-end quality from design through release and monitoring, and participate actively in story refinement, design reviews, code reviews, and incident response. Additionally, you will help onboard new team members and share knowledge through documentation and technical discussions, and apply AI tooling to improve your own productivity and share learnings with the team.

Requirements

4+ years of professional software engineering experience, including meaningful full-stack work.
Strong Python backend skills; FastAPI experience preferred. Comfortable with async programming, dependency injection, and structured API design.
Hands-on experience with event-driven systems (Kafka or equivalent) and designing for eventual consistency.
Solid PostgreSQL skills: schema design, query optimization, migrations, and data modeling at scale.
Production-level React experience: component architecture, state management, API integration, and UI testing.
You write high-quality, reusable, and maintainable code and hold that bar in code reviews.
You own problems end-to-end—from identifying the right solution through monitoring its production behavior.
You evaluate technical trade-offs clearly and communicate them to teammates and stakeholders.
You debug systematically, document what you’ve tried, and escalate strategically when blocked.
You articulate technical concepts clearly to both technical and non-technical audiences.
You contribute constructively to design reviews, sprint planning, and team retrospectives.
You embrace change, disagree and commit when needed, and stay calm under pressure.

Nice To Haves

Domain experience in shipping, logistics, carrier APIs, or rate selection.
Prior experience designing or building a rules engine, condition evaluation system, workflow engine, or decision tree end-to-end—both the API and the UI—from initial design through production delivery.
Experience working closely with ML or data science teams to bring model outputs into product surfaces.
Familiarity with LLM-based features or agent workflow systems.

Responsibilities

Build and maintain Python (FastAPI) services with async patterns suited to high-throughput, low-latency workloads.
Design and implement event-driven integrations (Kafka) to keep data products synchronized with upstream business events.
Architect PostgreSQL data models that balance query performance with auditability and long-term maintainability.
Develop APIs that power customer-facing data products—spanning business rules automation, ML-based recommendations, analytics, and configuration systems.
Contribute to API design, service decomposition, and cross-team technical reviews.
Build and own React UI surfaces for customer-facing data product features—including management interfaces, dashboards, and configuration tools.
Collaborate with design and product to translate requirements into polished, accessible interfaces without creating dependency on shared frontend capacity.
Integrate frontend surfaces with backend APIs across a range of data product types: rules engines, ML-powered features, reporting, and data exploration.
Maintain component quality, state management patterns, and end-to-end test coverage for the features you ship.
Contribute across the full spectrum of the Data Products team’s work—business rules automation, ML-based APIs, customer-facing analytics, and intelligent recommendation systems.
Partner with data science and ML teams to bring model outputs into reliable, well-instrumented production services.
Design systems with auditability in mind: versioning, immutable event logs, and traceable decision-making where the product requires it.
Evaluate and implement data product patterns appropriate to the problem—whether that’s a condition evaluation engine, a scoring API, or a configurable workflow.
Contribute to and deliver team-level quarterly goals, owning end-to-end quality from design through release and monitoring.
Participate actively in story refinement, design reviews, code reviews, and incident response.
Help onboard new team members and share knowledge through documentation and technical discussions.
Apply AI tooling to improve your own productivity and share learnings with the team.