Database Architect

WEX

. Own data architecture across multiple domains, modernizing legacy database systems and designing AI-native data infrastructure .

Posted 10/15/2026full-timeRemote • United StatesSeniorLead💰 $165,800 - $204,400 per yearWebsite

Tech Stack

Tools & technologies

AWSAzureCloudETLJavaKafkaMongoDBNeo4jNoSQLPostgresPythonSQLTerraform

About the role

Key responsibilities & impact

Own data architecture across multiple domains, modernizing legacy database systems and designing AI-native data infrastructure
Analyze and decompose large SQL Server stored procedures with embedded business logic and create migration strategies
Design patterns that separate business rules from data access and move business logic into application services
Lead refactoring aligned with domain-driven design, including bounded contexts, aggregates, and domain events
Implement event-driven patterns including change data capture, outbox patterns, and event sourcing where appropriate
Optimize query performance, indexing strategies, and execution plans
Create migration playbooks and tooling for stored procedure modernization
Design semantic data models optimized for AI retrieval and reasoning
Architect vector database solutions for RAG, including embeddings, chunking, similarity search, and hybrid retrieval
Design and implement embedding pipelines for AI agent consumption
Establish knowledge graph patterns, entity relationships, ontologies, and graph-based retrieval
Define data architectures for AI agent context, freshness, and consistency
Design RAG evaluation frameworks covering retrieval accuracy, relevance scoring, and feedback loops
Design canonical data models and schemas aligned with business domains
Architect solutions across relational, NoSQL, analytical, and vector database platforms
Design Kafka-based event streaming, materialized views, CQRS patterns, and real-time synchronization
Establish data platform patterns for pipelines, ETL/ELT orchestration, data quality, and observability
Define data residency, partitioning, and multi-region strategies
Create reference architectures for domain teams
Use AI coding assistants to accelerate database analysis, refactoring, and migration
Build AI-powered database engineering tools, including analysis, documentation, migration, and query optimization tools
Create AI-consumable artifacts such as structured documentation, annotated schemas, and context files
Author database architecture skills encoding patterns, constraints, and best practices
Develop prompts, workflows, and tooling for AI-assisted database modernization
Partner with AI/ML, domain, and application architecture teams
Contribute to Enterprise Architecture Council standards
Mentor engineers on database design, optimization, semantic modeling, and AI data infrastructure

Requirements

What you’ll need

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 experience decomposing complex stored procedures and migrating business logic to application services
Experience designing solutions across SQL Server, PostgreSQL, MongoDB, Cosmos DB, Snowflake, and data lakehouse platforms
Practical production experience with CDC, Kafka, outbox pattern, event sourcing, and CQRS
Data modeling expertise including canonical models, dimensional modeling, schema evolution, and extensibility
Hands-on experience with at least one vector database such as Pinecone, Weaviate, Milvus, pgvector, or Azure AI Search
Understanding of RAG architecture, embedding models, chunking strategies, retrieval optimization, hybrid search, and reranking
Experience designing semantic data structures for AI retrieval, knowledge representation, ontologies, or AI consumption
Understanding of embedding pipelines including text preprocessing, embedding generation, vector indexing, and incremental updates
Familiarity with LLM context requirements, token constraints, and context window optimization
2+ years actively using AI coding assistants for database work
Experience building tools, scripts, or automation leveraging AI/LLM capabilities
Familiarity with structured artifacts for AI consumption, including documented schemas, annotated procedures, and context files
Strong programming skills in at least one backend language: C#, Java, or Python
Cloud data services experience including Azure SQL, Cosmos DB, Azure AI Search, Azure Synapse, Snowflake, or AWS equivalents
Infrastructure-as-code experience with Terraform, ARM/Bicep, or CloudFormation
Understanding of domain-driven design and bounded contexts
Familiarity with data governance, lineage, and compliance requirements including HIPAA and PCI-DSS
Preferred: background in healthcare, benefits, payments, or similarly regulated industries
Preferred: experience building RAG systems or AI-powered search/retrieval applications
Preferred: knowledge graph experience with Neo4j, Amazon Neptune, or similar graph databases
Preferred: contributions to database tooling, AI/ML data infrastructure, or open-source projects
Preferred: experience mentoring engineers or leading database/data architecture communities of practice

Benefits

Comp & perks

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 eligibility for non-sales roles, based on role and applicable plan
Comprehensive and market competitive benefits designed to support personal and professional well-being