Senior Software Engineer – Semantic Data Lake

WEX

Senior Software Engineer designing and building scalable data models at WEX's enterprise data platform. Collaborating across teams to integrate and expose data assets with modern AI coding tools.

Posted 6/18/2026full-timeRemote • California, Illinois, Maine, Massachusetts, Texas, Washington • 🇺🇸 United StatesSenior💰 $121,500 - $145,500 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—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
Partner closely with the data products team to understand business requirements and ensure semantic models align with their needs
Implement logic for classifications, KPIs, scoring algorithms, and business rules, ensuring traceability and data lineage
Collaborate across teams to integrate with ingestion, MDM, and data product layers, and explore opportunities to expose 360 objects to LLM-powered and agentic applications

Requirements

What you’ll need

4-8 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, AI-assisted code review, and integrating LLMs or AI agents into engineering or data workflows
Experience building and scaling wide, entity-based tables and modeling domain concepts (e.g., customer, fleet, provider) into durable data objects
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, balancing business logic with platform scalability
A mindset for traceability, reproducibility, and semantic clarity—you build data models others (humans and AI systems alike) can trust and reuse
Bachelor's degree in Computer Science, Software Engineering, or related field

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
commission under an applicable plan
quarterly or annual bonus based on their role and applicable plan

ATS Keywords

✓ Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

SQLPythonScaladata transformationdata modelingdata quality practicesperformance optimizationdata lineageKPI implementationscoring algorithms

Soft Skills

collaborationcross-functional teamworkbusiness logic balancingtraceability mindsetsemantic clarity

Certifications

Bachelor's degree in Computer ScienceBachelor's degree in Software Engineering