Staff Software Engineer – Semantic Data Team

WEX

Staff Software Engineer designing and implementing scalable 360 data models at WEX. Collaborating with experts to integrate data across domains while leveraging AI tools for development.

Posted 6/10/2026full-timePortland • California, Illinois, Maine, Massachusetts, Washington • 🇺🇸 United StatesLead💰 $140,600 - $173,100 per yearWebsite

Tech Stack

Tools & technologies

PythonScalaSQL

About the role

Key responsibilities & 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
Develop and share patterns, prompts, and workflows that help the team get more leverage out of AI tooling
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 algorithms, and business rules, ensuring traceability and data lineage
Help define and enforce standards for data modeling, documentation, and governance within the semantic layer

Requirements

What you’ll need

8+ years of experience in data engineering or software engineering with a focus on data transformation, modeling, or analytics platforms
Strong proficiency in SQL and at least one general-purpose language such as Python or Scala
Demonstrated experience as an AI-native engineer—using tools like Claude, GitHub Copilot, Cursor, or similar as part of your everyday development workflow
Comfort with modern AI engineering practices such as prompt design, context engineering, Spec-Driven Development (SDD)
Experience building and scaling wide, entity-based tables and modeling domain concepts (e.g., customer, fleet, provider)
Solid understanding of data quality practices—including validation, enrichment, schema enforcement, and business rule encoding
Experience working with large-scale datasets and optimizing transformation pipelines for performance and maintainability
Comfort operating in a collaborative, cross-functional environment
A mindset for traceability, reproducibility, and semantic clarity
Bachelor's degree in Computer Science, Software Engineering, or related field
A Master's or PhD in Data Science, Machine Learning, Artificial Intelligence, Computer Science, or Statistics is a big plus.

Benefits

Comp & perks

health, dental and vision insurances
retirement savings plan
paid time off
health savings account
flexible spending accounts
life insurance
disability insurance
tuition reimbursement
bonuses

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

SQLPythonScaladata transformationdata modelingdata analyticsdata quality practicestransformation pipelinesKPI logicbusiness rule encoding

Soft Skills

collaborativecross-functionaltraceabilityreproducibilitysemantic clarity

Certifications

Bachelor's degree in Computer ScienceBachelor's degree in Software EngineeringMaster's degree in Data SciencePhD in Data ScienceMaster's degree in Machine LearningMaster's degree in Artificial IntelligenceMaster's degree in Statistics