Principal Software Engineer, Semantic Data Services

WEX•Boston, MA

4d•$200,600 - $250,400

About The Position

WEX is reimagining its enterprise data platform to make data understandable to people, applications, AI models, and autonomous agents. The Principal Software Engineer will help build the next generation of WEX's Data-as-a-Service platform and the semantic foundation connecting enterprise data with business meaning. The role involves defining and building trusted semantic objects for major business domains, combining data, relationships, definitions, derived attributes, policies, lineage, and context into reusable assets for analytics, data products, decisioning, and AI experiences. This is a senior technical leadership role that remains hands-on. The engineer will partner with engineering, architecture, product, AI, analytics, risk, finance, and business teams across WEX to address complex data and distributed systems problems and help shape the future of enterprise data platforms in an AI-native environment.

Requirements

10+ years of experience in software engineering, data engineering, distributed systems, data platforms, or related technology areas, with demonstrated experience operating at Staff, Principal, or equivalent technical scope.
Deep software engineering and distributed systems expertise, including experience designing and building large-scale production platforms.
Deep understanding of modern data architecture, including large-scale data processing, streaming, lakehouse architectures, data products, and distributed systems.
Deep understanding of semantic data technologies and industry direction; direct experience building a semantic data layer is strongly recommended.
Experience with semantic modeling, ontology, metadata platforms, knowledge graphs, data catalogs, enterprise data modeling, or closely related technologies.
Ability to translate complex business concepts into scalable technical abstractions and reusable platform capabilities.
Strong understanding of data quality, governance, lineage, security, privacy, and operational reliability.
Experience building platforms or capabilities adopted by multiple engineering teams, business domains, or product organizations.
Strong architectural judgment and ability to reason through complex tradeoffs while moving between architecture and detailed implementation.
Ability to influence technical direction and drive alignment across teams and organizational boundaries.
Strong communication skills and ability to explain complex technical concepts to engineers, product teams, business partners, and senior leaders.

Nice To Haves

Experience building platforms that support AI/ML, generative AI, RAG, or agentic applications.
Experience with knowledge representation, semantic search, context engineering, graph technologies, or AI-ready enterprise data.
Experience modernizing large enterprise data ecosystems with multiple business domains and legacy systems.
Experience with Spark, Flink, Kafka, Iceberg, Snowflake, Databricks, cloud-native data services, graph databases, or equivalent large-scale data technologies.
Experience defining reusable frameworks, APIs, standards, or platform capabilities broadly adopted beyond an individual team.

Responsibilities

Define and influence the architecture and technical direction for WEX's Semantic Data Lake and next-generation Data-as-a-Service platform.
Design and build semantic business objects that combine enterprise data, business context, relationships, metrics, derived attributes, rules, lineage, quality, and governance.
Develop scalable patterns and frameworks for creating semantic objects across business lines while maintaining consistent enterprise standards.
Build platform capabilities across semantic modeling, ontology, metadata, knowledge graphs, data quality, lineage, data contracts, and governance.
Work with business and product teams to translate complex business concepts into durable technical models and reusable platform capabilities.
Help capture business context from databases, applications, workflows, documents, policies, and institutional knowledge.
Enable AI and agentic applications to discover, understand, reason over, and safely act on trusted enterprise data.
Design reusable APIs, services, frameworks, and developer experiences that help teams build data products and AI experiences.
Solve distributed systems, data processing, scalability, reliability, and performance challenges.
Establish engineering patterns and architectural standards and influence adoption across teams.
Mentor engineers and provide technical guidance on complex architecture and implementation decisions.
Remain hands-on with architecture, design, prototyping, code, and critical platform components.

Benefits

Health insurance
Dental insurance
Vision insurance
Retirement savings plan
Paid time off
Health savings account
Flexible spending accounts
Life insurance
Disability insurance
Tuition reimbursement
Quarterly or annual bonus eligibility for non-sales roles, subject to role and applicable plan