Principal Software Engineer - Data

As a Principal Staff Software Engineer, you will play a pivotal role in shaping WEX's DaaS platform end-to-end. You will drive the unification of data acquisition, semantic modeling, and data products, ensuring they operate together as a coherent, scalable, and trusted foundation for analytics, AI, and customer-facing experiences.

This is not just a technical role-it is a platform architect and multiplier role, where you'll be responsible for defining cross-cutting patterns, guiding teams across domains, and raising the technical bar across WEX's data ecosystem. If you're motivated by solving platform problems at global scale, influencing enterprise direction, and leaving behind systems that endure, this is your role.

• Architect the DaaS platform end-to-end: Define the next generation of WEX's enterprise data stack spanning ingestion, semantic data modeling, metadata, and product delivery.

• Establish platform standards: Set reusable frameworks for ingestion, modeling, lineage, observability, and access control that accelerate adoption across domains.

• Guide technical strategy at scale: Partner with senior engineering, product, and business leaders to align data architecture with WEX's strategic objectives.
  Solve for scale, reliability, and trust: Design systems that handle billions of records, guarantee semantic consistency, and deliver auditable, governed data assets.
  Mentor and multiply: Coach senior staff engineers and architects, instilling best practices in distributed systems, platform reliability, and semantic clarity.

• Drive innovation: Explore and incorporate modern open-source and cloud-native technologies (e.g., Spark, Iceberg, Kafka, Delta, DBT, Ray, ML-ready data services).

• Be the bridge: Collaborate across Data Acquisition, Semantic Modeling, Data Products, and Governance teams to ensure WEX's data is trusted, consistent, and usable across every business domain.

• 12-15+ years of experience in software or platform engineering, with a proven track record of building and scaling large-scale data platforms.
  Expertise in distributed systems, data acquisition, and semantic modeling, with architectural ownership of systems processing tens of millions to billions of records per day.

• Demonstrated ability to set cross-domain architectural standards and influence adoption across multiple engineering teams.

• Strong background in data lifecycle management (versioning, auditability, observability, lineage, reproducibility).

• Deep experience with modern data ecosystems: streaming (Kafka, Flink), batch (Spark, DBT), storage (Iceberg, Delta), orchestration (Airflow, Dagster), and APIs.

• Exceptional communication and leadership skills-you can inspire engineers, influence executives, and build consensus across technical and business stakeholders.

• A passion for creating platforms that endure: trusted, consistent, and empowering for analytics, AI, and products enterprise-wide.