Staff Software Engineer Semantic Data Team - wex

This is a remote position; however, the candidate must reside within 30 miles of one of the following locations: Portland, ME; Boston, MA; Chicago, IL; San Francisco Bay Area, CA; and Seattle/WA.

About the Team/Role

WEX is reimagining its enterprise data platform with a powerful goal: transforming raw data into semantically meaningful, reusable, and trusted business assets. As a Staff Software Engineer on the Semantic Data Team, you'll play a critical role in designing, building, and maintaining our core 360 data objects—such as Customer360, Fleet360, and Provider360.

These wide, entity-based tables are foundational to our analytics, AI, and product platforms. You'll implement rich transformation logic, encode business rules, and ensure data consistency across domains, making our data models both technically scalable and business-ready.

This team is at the heart of WEX's DaaS platform—bridging raw data with meaningful business insights. You'll help define and deliver the semantic backbone of our products, analytics, and machine learning systems.

We're looking for an AI-native engineer: someone who builds with modern AI coding tools (Claude, Copilot, Cursor, and similar) and Spec-Driven Development (SDD) as a core part of their daily workflow, not an occasional add-on. You'll use these tools to accelerate design, generate and refactor transformation logic, write tests, document semantics, and explore data—while applying the engineering judgment needed to ship production-grade, trustworthy data assets.

If you're excited about building semantic models that carry real-world meaning, scale to billions of records, and unify how a business understands its world—and doing it with the leverage of modern AI tooling—this is your next big move.

How you'll make an impact

Design and implement semantically consistent, scalable 360 data models that integrate data across domains.

Build and maintain transformation pipelines that apply cleansing, standardization, enrichment, and derived logic to domain datasets.

Write production-quality, testable code in SQL and Python (or equivalent)—delivering performant and maintainable data assets.

Leverage AI coding assistants (Claude, Copilot, Cursor, and similar) to accelerate development—drafting transformation logic, generating tests, refactoring pipelines, exploring datasets, and producing semantic documentation—while critically reviewing AI output for correctness, performance, and alignment with business rules.

Develop and share patterns, prompts, and workflows that help the team get more leverage out of AI tooling, raising the bar for AI-native engineering practices across the Semantic Data Team.

Work closely with domain experts, data scientists, and product stakeholders to translate business concepts into interpretable, decision-ready data models.

Implement logic for classifications, KPIs, scoring al