Principal Database Engineer – SQL Server & AI Data Infrastructure

WEXWEXUS•Portland, ME

3d•$165,800 - $204,400

About The Position

WEX is seeking a highly experienced Principal Database Engineer with deep expertise in SQL Server and T-SQL to modernize and scale critical data platforms. This hands-on engineering role involves solving complex database performance, scalability, and modernization challenges at an enterprise scale. The engineer will collaborate with application engineering, SRE, operations, and architecture teams, independently identifying problems, driving solutions, and taking ownership from design through production. The team is also integrating AI capabilities into database engineering, including AI-assisted development, automation, semantic search, embeddings, and vector-based data infrastructure.

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.

Nice To Haves

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.
Experience with event streaming technologies such as Kafka.
Familiarity with NoSQL and document databases.

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.