Principal Software Engineer - Semantic Data Platform Lead

WEX, Inc.; Portland (ME); On-site; USD 201,000 - 250,000; Full time

Job summary

WEX, Inc. is seeking a Principal Software Engineer to shape the semantic foundation of our Data-as-a-Service platform. You will define architecture, build semantic objects, and drive cross-team collaboration across data, product, AI, and risk orgs.

The role combines senior technical leadership with hands-on engineering to solve distributed systems, data processing, and governance challenges in an AI-native data landscape.

Qualifications

• More than 10 years in software/data engineering or related fields.
• Experience designing large-scale production platforms.
• Expertise in semantic data technologies and knowledge graphs.
• Ability to translate business concepts into scalable abstractions.
• Strong communication and leadership across multiple teams.

Responsibilities

• Define architecture and technical direction for the semantic data lake and DaaS.
• Build semantic business objects with data, context, lineage, and governance.
• Create scalable patterns for semantic objects across lines of business.
• Develop platform capabilities for ontology, metadata, data quality, and governance.
• Collaborate with product, AI, analytics, risk, and finance teams.
• Mentor engineers and influence architectural standards without authority.
• Remain hands-on with critical platform components and prototyping.

Skills

Staff-level leadership

Distributed systems

Semantic data

Architectural judgment

Data platform design

Mentoring engineers

Hands-on engineering

Tools

Spark

Flink

Kafka

Iceberg

Snowflake

Databricks

Graph databases

Job description

WEX, Inc. is seeking a Principal Software Engineer to shape the semantic foundation of our Data-as-a-Service platform. You will define architecture, build semantic objects, and drive cross-team collaboration across data, product, AI, and risk orgs.

The role combines senior technical leadership with hands-on engineering to solve distributed systems, data processing, and governance challenges in an AI-native data landscape.