Senior Database Architect

WEX Inc.; United States; On-site; USD 150,000 - 230,000; Full time

Job summary

WEX Inc. seeks a Senior Database Architect who combines deep SQL Server expertise with a vision for AI-native data infrastructure. You will modernize legacy stored procedures and migrate logic to domain services to enable scalable AI workflows.

You will design vector databases, embedding pipelines, and semantic models for AI agents, while shaping a cross‑platform data platform across SQL Server, PostgreSQL, MongoDB/Cosmos DB, Snowflake and vector stores.

Qualifications

• 8–12 years in database engineering and architecture.
• Deep SQL Server expertise: T-SQL optimization, stored procedures, and performance tuning.
• Experience decomposing complex stored procedures and migrating logic to services.
• Multi-platform data architecture across relational, NoSQL, and analytical platforms.
• Event-driven patterns: CDC, outbox, CQRS, and related practices.

Responsibilities

• Analyze and decompose large SQL Server stored procedures (1,000+ lines) with embedded business logic.
• Design patterns to separate business rules from data access and migrate logic to application services.
• Lead refactoring to align database structures with domain-driven design and events.
• Implement event-driven patterns to decouple systems from direct DB dependencies.
• Optimize queries, indexing, and execution plans as part of modernization.
• Create migration playbooks and tooling for stored procedure modernization.

Skills

SQL Server

T-SQL

Stored procedures

Data modeling

Event-driven

Vector databases

RAG architecture

Semantic modeling

Embedding pipelines

Cross-platform design

Tools

Kafka

Snowflake

MongoDB

Cosmos DB

Job description

We are seeking a Senior Database Architect who combines deep expertise in legacy database systems with forward-looking vision for AI-native data architecture. You'll lead the decomposition of complex stored procedures while simultaneously designing the vector databases, embedding strategies, and semantic models that power our AI agents and workflows. This is an AI-first role in two senses: you'll leverage AI to accelerate your own work (stored procedure analysis, migration generation, schema documentation), and you'll design the data infrastructure that AI systems depend on. If you're excited about both solving hard legacy database problems and architecting the data layer for AI-native applications, this role is for you.

What You'll Do

Legacy Database Modernization

• Analyze and decompose large SQL Server stored procedures (1,000+ lines) with embedded business logic, creating migration strategies that extract logic into domain services
• Design patterns for separating business rules from data access, enabling stored procedures to become thin data-access layers while business logic moves to application services
• Lead refactoring efforts that align database structures with domain-driven design: bounded contexts, aggregates, and domain events
• Implement event-driven patterns that decouple systems from direct database dependencies: change data capture, outbox patterns, event sourcing where appropriate
• Optimize query performance, indexing strategies, and execution plans as part of modernization efforts
• Create migration playbooks and tooling that engineering teams can apply to their own stored procedure modernization

AI Data Infrastructure & Semantic Modeling

• Design semantic data models that capture domain knowledge in structures optimized for AI retrieval and reasoning
• Architect vector database solutions for RAG implementations: embedding strategies, chunking approaches, similarity search optimization, and hybrid retrieval patterns
• Design and implement embedding pipelines that transform domain content into vector representations suitable for AI agent consumption
• Establish knowledge graph patterns where appropriate: entity relationships, ontologies, and graph-based retrieval for complex domain reasoning
• Define data architectures for AI agent context: what data agents need, how it's structured, how freshness and consistency are maintained
• Design evaluation frameworks for RAG quality: retrieval accuracy, relevance scoring, and feedback loops for continuous improvement
• Modernize data platform architecture: design canonical data models and schemas that are flexible, extensible, and aligned with business domain concepts

Modern Data Platform Architecture

• Design canonical data models and schemas that are flexible, extensible, and aligned with business domain concepts
• Architect data solutions across multiple platforms: SQL Server, PostgreSQL, MongoDB/Cosmos DB, Snowflake, and vector databases (Pinecone, Weaviate, pgvector, Azure AI Search)
• Design event-driven data flows: Kafka-based event streaming, materialized views, CQRS patterns, and real-time data synchronization
• Establish data platform infrastructure patterns: data pipelines, ETL/ELT orchestration, data quality frameworks, and observability
• Define data residency, partitioning, and multi-region strategies for performance and compliance
• Create reference architectures for common data patterns that domain teams can adopt

AI-First Database Engineering

• Leverage AI coding assistants (GitHub Copilot, Cursor, Claude Code) to accelerate stored procedure analysis, refactoring, and migration
• Build AI-powered tools for database engineering: automated stored procedure analysis, schema documentation generators, migration assistants, and query optimization recommenders
• Create AI-consumable artifacts: structured documentation, annotated schemas, and context files that enable AI agents to understand and work with database systems
• Author database architecture skills that encode patterns, constraints, and best practices for AI-assisted development
• Develop prompts, workflows, and tooling that help engineering teams apply AI effectively to database modernization tasks

Cross-Domain Leadership

• Partner with AI/ML teams to ensure data architecture supports agent and workflow requirements
• Collaborate with domain teams to understand their data requirements and design solutions aligned with domain ownership
• Work with application architects to ensure data architecture supports service-oriented and event-driven designs
• Contribute to Enterprise Architecture Council (EAC) standards for data architecture, modeling conventions, and technology selection
• Mentor engineers on database design, optimization, semantic modeling, and AI data infrastructure

What You’ll Bring

Required Experience

• 8-12 years in database engineering and architecture, with significant experience in enterprise-scale SQL Server environments
• Deep SQL Server expertise: T-SQL optimization, stored procedure design and refactoring, query plan analysis, indexing strategies, and performance tuning
• Hands-on modernization experience: track record of decomposing complex stored procedures and migrating business logic to application services
• Multi-platform data architecture: experience designing solutions across relational (SQL Server, PostgreSQL), NoSQL (MongoDB, Cosmos DB), and analytical (Snowflake, data lakehouse) platforms
• Event-driven data patterns: CDC, Kafka, outbox pattern, event sourcing, CQRS - practical experience implementing these in production
• Data modeling expertise: canonical models, dimensional modeling, schema evolution, and designing for extensibility
• AI & Semantic Data Competencies: Vector database experience, RAG architecture understanding, Semantic modeling, understanding of embedding pipelines, familiarity with LLM context requirements

Preferred Experience

• Background in healthcare, benefits, payments, or similarly regulated industries
• Experience building RAG systems or AI-powered search/retrieval applications
• Knowledge graph experience: Neo4j, Amazon Neptune, or similar graph databases
• Contributions to database tooling, AI/ML data infrastructure, or open-source projects
• Experience mentoring engineers or leading database/data architecture communities of practice

The base pay range represents the anticipated low and high end of the pay range for this position. Actual pay rates will vary and will be based on various factors, such as your qualifications, skills, competencies, and proficiency for the role. Base pay is one component of WEX's total compensation package. Most sales positions are eligible for commission under the terms of an applicable plan. Non-sales roles are typically eligible for a quarterly or annual bonus based on their role and applicable plan.

WEX's comprehensive and market competitive benefits are designed to support your personal and professional well-being. Benefits include health, dental and vision insurances, retirement savings plan, paid time off, health savings account, flexible spending accounts, life insurance, disability insurance, tuition reimbursement, and more.

WEX is a global commerce platform that helps businesses solve for operational complexities like employee benefits, managing and mobilizing fleets, and streamlining payments. With over 6,500 employees, we work with large and small companies in more than 200 countries and territories, and can tailor our services to meet the unique needs of their businesses.

We hire people who share our passion for continuous innovation and client service that is unparalleled in the industry.

WEX is an equal opportunity employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex, race, color, age, national origin, religion, sexual orientation, gender identity, protected veteran status, disability or other protected status.

WEX promotes a drug-free workplace. Qualified individuals with a disability have the right to request a reasonable accommodation. If you require a reasonable accommodation as a result of your disability at any point in the job application process, please submit your request through our Reasonable Accommodation Request Form. This form is for accommodation requests only and cannot be used to inquire about the status of applications.