[Hiring] Database Architect @WEX

Role Description

Owns data architecture across multiple domains, with dual focus:

• Modernizing legacy database systems—particularly large-scale SQL Server environments with complex stored procedures containing embedded business logic.
• Designing AI-native data infrastructure—semantic data models, vector databases, and RAG architectures that power AI agents and workflows.

Establishes patterns for:

• Domain-driven data models
• Event-driven data flows
• Canonical schemas across relational, NoSQL, analytical, and AI-optimized data platforms.

Qualifications

• 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.

Requirements

• Vector database experience: hands-on with at least one vector DB (Pinecone, Weaviate, Milvus, pgvector, Azure AI Search, or similar).
• RAG architecture understanding: embedding models, chunking strategies, retrieval optimization, hybrid search, and reranking patterns.
• Semantic modeling: experience designing data structures optimized for AI retrieval—knowledge representation, ontologies, or domain-specific schemas for AI consumption.
• Understanding of embedding pipelines: text preprocessing, embedding generation, vector indexing, and incremental updates.
• Familiarity with LLM context requirements: what data AI agents need, token constraints, context window optimization.

Benefits

• Health, dental, and vision insurances
• Retirement savings plan
• Paid time off
• Health savings account
• Flexible spending accounts
• Life insurance
• Disability insurance
• Tuition reimbursement
• Quarterly or annual bonus based on role and applicable plan

Company Description

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.

Pay Range: $165,800.00 - $204,400.00