Principal Database Engineer - SQL Server & AI Data Infrastructure [Remote]

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Principal Database Engineer – SQL Server & AI Data Infrastructure based in United States.

The Principal Database Engineer will help modernize and scale enterprise data platforms that support critical business applications and next-generation AI capabilities. This is a deeply technical, hands-on role focused on SQL Server, T-SQL, database performance, scalability, and modernization. You will work with high-volume environments containing complex data relationships and business-critical workloads. The role combines traditional database engineering expertise with cloud data platforms, automation, event-driven architectures, and AI-enabled engineering practices. You will partner across application engineering, SRE, operations, architecture, and AI/ML teams while independently driving complex initiatives from design through production. This is an opportunity to remain highly technical while having Senior Staff-level ownership and influence over the evolution of modern data infrastructure.

• Design, develop, optimize, and modernize large-scale SQL Server databases and data platforms, with a strong focus on scalability, maintainability, reliability, and long-term technical health.
• Analyze and refactor complex T-SQL, stored procedures, functions, and database logic while identifying opportunities to simplify and improve legacy systems.
• Diagnose and resolve database performance challenges through execution-plan analysis, indexing strategies, query optimization, database tuning, and detailed analysis of database internals.
• Drive schema modernization and migration initiatives, developing automation and implementation strategies that protect data integrity and minimize disruption to business-critical systems.
• Engineer replication, synchronization, data integration, and data movement patterns across transactional and analytical environments, including SQL Server, PostgreSQL, Snowflake, and cloud data services.
• Design and support high-volume OLTP and OLAP environments while applying strong knowledge of indexing, locking, transactions, isolation levels, concurrency, and query optimization.
• Implement event-driven database patterns such as Change Data Capture, outbox patterns, and event publishing to support modern distributed architectures.
• Apply AI coding assistants and emerging AI technologies to accelerate development, debugging, documentation, modernization, and database engineering workflows.
• Contribute to AI-enabled data infrastructure, including embedding pipelines, vector databases, semantic search, retrieval systems, and data capabilities supporting AI applications and agentic workflows.
• Independently lead complex database engineering initiatives from problem definition through design, implementation, deployment, and production adoption.
• Serve as a technical authority for complex database and performance challenges, providing guidance through design reviews, code reviews, engineering standards, and technical decision-making.
• Mentor other engineers and contribute to the development of scalable database engineering practices, standards, tooling, and automation.
• Investigate high-impact production incidents using database metrics, logs, CPU and memory utilization, execution plans, and observability data, driving root-cause analysis and durable corrective actions.
• Collaborate closely with application engineering, SRE, operations, architecture, data engineering, and AI/ML teams to ensure reliable delivery and continuous improvement of critical data platforms.

Requirements

• 15+ years of experience in database engineering, data platform engineering, software engineering, or a related technical discipline, with substantial experience operating at enterprise scale.
• Deep hands-on expertise with Microsoft SQL Server and T-SQL, including complex stored procedures, execution-plan analysis, indexing, query optimization, database tuning, and performance troubleshooting.
• Demonstrated experience modernizing, refactoring, or transforming legacy database environments rather than simply maintaining existing systems.
• Strong experience supporting large-scale, high-volume, business-critical databases and applications where reliability, performance, and data integrity are essential.
• Strong programming skills in Python, C#, or a comparable language, with the ability to develop automation, engineering tools, integrations, and data-processing solutions.
• Experience with data pipelines, ETL/ELT, data integration, batch processing, and/or event-driven architectures, along with a strong understanding of distributed data workflows.
• Deep knowledge of database internals, transaction management, concurrency, locking, isolation levels, indexing, and performance optimization.
• Experience using AI coding assistants such as GitHub Copilot, Cursor, Claude Code, Augment, or similar tools to accelerate engineering work.
• Familiarity with AI data technologies and concepts such as embeddings, vector databases, semantic search, retrieval-augmented generation, or AI-agent data infrastructure, with the ability and willingness to develop AI-enabled data tooling.
• Experience with or exposure to modern data and cloud technologies such as PostgreSQL, Snowflake, Azure SQL, Cosmos DB, AWS data services, or comparable platforms.
• Experience with infrastructure-as-code technologies such as Terraform, ARM, Bicep, or similar tools, as well as CI/CD, source control, database migrations, schema versioning, and deployment automation.
• Familiarity with event streaming technologies such as Kafka and NoSQL or document databases is a plus.
• Experience in payments, financial services, healthcare, benefits, or other highly regulated environments is preferred, as is experience supporting highly available, customer-facing or business-critical systems.
• Oracle PL/SQL experience, hands-on RAG or semantic-search development, vector database expertise, and experience building AI-powered internal engineering tools are additional advantages.
• Strong analytical, problem-solving, communication, collaboration, and technical leadership skills, with the ability to independently identify complex problems, make sound engineering decisions, and drive initiatives through completion.

Benefits

• Base salary range of $165,800 to $204,400 annually, with actual compensation determined based on qualifications, skills, competencies, experience, and proficiency for the role.
• Eligibility for a quarterly or annual performance-based bonus, depending on the applicable compensation plan.
• Comprehensive health, dental, and vision insurance options.
• Retirement savings plan to support long-term financial wellbeing.
• Paid time off for personal time, rest, and work-life balance.
• Health Savings Account and Flexible Spending Account options.
• Life insurance and disability insurance coverage.
• Tuition reimbursement to support continued learning and professional development.
• Fully remote work arrangement within the United States.
• Opportunity to work on large-scale SQL Server modernization, cloud data platforms, and AI-enabled infrastructure.
• Hands-on exposure to emerging technologies including generative AI, embeddings, vector databases, semantic search, RAG, agentic workflows, and AI-assisted engineering.
• Significant technical ownership and influence over critical enterprise data platforms and engineering practices.
• Collaboration with application engineering, SRE, operations, architecture, data, and AI/ML teams in a highly technical environment.
• Inclusive workplace committed to diversity, belonging, equal opportunity, and reasonable accommodations.