Principal Software Engineer, Semantic Data Services

WEXWEXUS•Francisco, IN

1d•$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 its semantic foundation, connecting enterprise data with business meaning. The role will define and build trusted semantic objects for major business domains, bringing together data, relationships, business definitions, derived attributes, policies, lineage, and context as reusable assets for analytics, data products, decisioning, and AI experiences. The engineer will serve as a senior technical leader and hands-on contributor, partnering with engineering, architecture, product, AI, analytics, risk, finance, and business teams to solve complex data and distributed systems problems.

Requirements

10 or more years of experience in software engineering, data engineering, distributed systems, data platforms, or related technology areas, with demonstrated experience 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 working across architecture and detailed implementation.
Ability to influence technical direction and drive alignment across teams and organizational boundaries.
Strong communication skills 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 technologies such as 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 multiple lines of business 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.
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 faster.
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, based on role and applicable plan