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# SQL Server Architect

- **Company:** Aziro Technologies Llc
- **Location:** Atlanta, United States
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Code Review, Databases, Continuous Integration, Data Infrastructure, Data Systems, Cursor, Database Development, Microsoft SQL Server, SQL Azure, Packet Analyzer, Query Optimization, Search Technologies, Database Engines, Scripting, GitHub Copilot, Delivery Pipeline, Large Language Models, HybridCloud, Git, Cloudformation, Enterprise Integration, Cloud Migration, Terraform
- **Published:** September 17, 2026
- **Apply:** https://www.dice.com/job-detail/9fd838e4-5bcc-44fa-b727-7b3bd51e4418

## About the Role

· Deep SQL Server architecture & internals - query engine, storage engine, transaction/locking/isolation levels, execution plan internals; 15+ yrs hands-on, architect-level design authority (not admin-level)

· HA/DR design mastery - Always On AGs, clustering, replication topologies; able to architect DR strategy across on-prem VMs and hybrid cloud, not just configure it

· Cloud migration engineering - hands-on RDS for SQL Server (and/or Azure SQL/MI) migration mechanics: DMS, native backup/restore, licensing model trade-offs (BYOL vs. License Included)

· Strong Python scripting - automation, tooling, and integration development; not "can write a script" but production-grade automation engineering

· AI-assisted engineering fluency - daily hands-on use of AI coding assistants (GitHub Copilot, Claude Code, Cursor, or similar) to accelerate schema design, query optimization, and code review

· LLM/agentic infrastructure exposure - working knowledge of embeddings, vector databases, RAG, and semantic search as they intersect with data platform design

· AI-enabled database operations - experience evaluating or building AI-driven observability, anomaly detection, or self-healing/auto-remediation tooling for database platforms

· MCP / tool-integration awareness - familiarity with Model Context Protocol or comparable frameworks for connecting AI agents to data systems

· Performance engineering at scale - wait-stats methodology, indexing strategy, parameter sniffing mitigation - demonstrable via live plan-reading, not resume claims

· IaC & CI/CD fluency - Terraform/CloudFormation, Git, automated pipelines for database deployment and change management