Principal Database Engineer - SQL Server & AI Data Infrastructure

Principal Database Engineer - SQL Server & AI Data Infrastructure The Opportunity

WEX is looking for a highly experienced Database Engineer to help modernize and scale critical data platforms while supporting the next generation of AI-enabled applications.

This is a hands-on engineering role for someone who brings deep expertise in SQL Server and T-SQL, combined with the ability to solve complex database performance, scalability, and modernization challenges at enterprise scale.

You will work across large, business-critical data environments, partnering closely with application engineering, SRE, operations, and architecture teams. The role is highly technical and execution-oriented-you will be expected to independently identify problems, drive solutions, and take ownership from design through implementation and production.

The team is also applying modern AI capabilities to database engineering, including AI-assisted development, automation, semantic search, embeddings, and vector-based data infrastructure.

• 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 Git Hub 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.

• 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,…