Principal Database Engineer – SQL Server & AI Data Infrastructure 

WEX is seeking a highly experienced Database Engineer to modernize and scale critical data platforms supporting business-critical systems and AI-enabled applications. The role focuses on SQL Server and T-SQL engineering, database performance and modernization, enterprise-scale data platforms, AI-enabled data infrastructure, technical leadership, and production problem solving.

Responsibilities:

• Design, develop, optimize, and modernize large-scale SQL Server databases and data platforms
• Analyze and refactor complex T-SQL, stored procedures, functions, and database logic
• Identify and resolve database performance bottlenecks through execution-plan analysis, indexing, query optimization, and database tuning
• Drive schema improvements and database modernization initiatives that improve scalability, maintainability, and reliability
• Develop migration strategies and automation that maintain data integrity and minimize disruption to business-critical systems
• Implement and improve data replication and synchronization patterns across transactional and analytical environments
• Apply event-driven database patterns such as Change Data Capture (CDC), outbox patterns, and event publishing
• Engineer solutions for large, high-volume databases supporting critical business applications and partners
• Work with databases containing terabytes of data and complex data relationships
• Develop data pipelines and integration patterns across SQL Server, PostgreSQL, Snowflake, and cloud data services
• Support both OLTP and OLAP environments and optimize data movement between systems
• Apply strong understanding of database internals, including indexing, locking, transactions, isolation levels, concurrency, and query optimization
• Use modern AI coding assistants such as GitHub Copilot, Cursor, Claude Code, or similar tools to accelerate development, analysis, debugging, and modernization
• Explore and implement AI-powered approaches for analyzing stored procedures, documenting schemas, and automating database engineering workflows
• Contribute to AI-native data infrastructure, including embedding pipelines, vector databases, semantic search, and retrieval systems
• Develop data and retrieval capabilities that support AI applications and agentic workflows
• Evaluate emerging AI tools and determine where they can improve engineering productivity and data platform capabilities
• Independently lead complex database engineering initiatives from problem definition through production implementation
• Serve as a technical resource for complex database and performance challenges
• Partner effectively with application engineering, SRE, operations, architecture, and AI/ML teams
• Provide technical guidance through code reviews, design discussions, and engineering standards
• Mentor other engineers and contribute to the development of database engineering practices
• Take ownership of outcomes rather than simply completing assigned tasks
• Participate in resolving high-impact production issues involving critical database systems
• Diagnose complex problems using logs, database metrics, CPU/memory utilization, execution plans, and other observability data
• Quickly determine root cause, coordinate with the appropriate technical teams, and drive issues through resolution
• Balance immediate incident resolution with longer-term improvements that prevent recurrence

Requirements:

• 15+  years of experience in database engineering, data platform engineering, software engineering, or a related technical discipline
• Deep hands-on experience with Microsoft SQL Server and T-SQL, including complex stored procedures, query optimization, execution-plan analysis, indexing, and performance tuning
• Demonstrated experience modernizing or refactoring legacy database systems, not simply maintaining existing environments
• Experience working with large-scale, business-critical databases and high-volume data environments
• Strong programming skills in Python, C#, or a similar language for automation, tooling, and data processing
• Experience with data pipelines, ETL/ELT, data integration, batch processing, and/or event-driven architectures
• Strong understanding of database internals, transaction management, concurrency, locking, and performance optimization
• Experience working across engineering teams and independently driving complex technical initiatives
• Experience using AI coding assistants such as Cursor, GitHub Copilot, Claude Code, Augment, or similar tools
• Familiarity with embeddings, vector databases, semantic search, or RAG concepts
• Experience with or willingness to build AI-enabled data tooling and automation
• Exposure to technologies such as PostgreSQL, Snowflake, Azure SQL, Cosmos DB, AWS data services, or similar platforms
• Experience with infrastructure-as-code such as Terraform, ARM/Bicep, or similar technologies
• Experience with CI/CD, source control, database migrations, schema versioning, and deployment automation
• Experience with event streaming technologies such as Kafka is a plus
• Familiarity with NoSQL and document databases is a plus
• Experience in payments, financial services, healthcare, benefits, or other highly regulated environments
• Experience supporting highly available, customer-facing or business-critical systems
• Experience with Oracle PL/SQL in addition to SQL Server
• Hands-on experience with RAG, semantic search, vector databases, or AI-agent data infrastructure
• Experience building internal engineering tools or automation using AI