Senior Database Engineer

Datavail is hiring a Senior Database Engineer/SQL Server DBA to support mission-critical database systems for clients. The role serves as a primary DBA and trusted technical advisor, leading database service delivery, performance and risk management, cloud architecture guidance, and automation.

Responsibilities:

• Serve as a trusted advisor to clients, proactively identifying performance, availability, and security risks before they become incidents
• Advise clients on cloud database architecture, migration, and cost optimization across AWS and Azure (IaaS and PaaS)
• Lead architecture design, disaster recovery planning, and capacity forecasting initiatives
• Own the end-to-end database service lifecycle — backup strategy, HA/DR configuration, proactive tuning, and platform roadmap planning
• Define and track service-level objectives (SLOs) for database availability and performance, and drive automated remediation for recurring failure patterns rather than manually resolving the same issue repeatedly
• Lead root-cause analysis and post-incident reviews for major issues, translating findings into automation or process changes that prevent recurrence
• Design and implement scalable database structures, including partitioning strategies and audit specifications
• Develop and maintain deployment/rollback scripts and coordinate version updates across environments
• Build automation (Python, PowerShell) for backup validation, monitoring, alerting, and reporting integrations (e.g., Power BI)
• Migrate/support SSIS packages and SSAS cubes, and develop stored procedures for reporting
• Collaborate directly with client technical teams and executive stakeholders, translating technical findings into business-relevant recommendations

Requirements:

• T-SQL query optimization — reading and rewriting execution plans, resolving parameter sniffing, statistics/cardinality issues, and Query Store-based tuning
• Rewriting and refactoring existing stored procedures and T-SQL code for performance — not just tuning execution plans, but redesigning logic and set-based approaches where needed
• Indexing strategy — designing and maintaining clustered/nonclustered/covering indexes, evaluating columnstore where appropriate, and managing fragmentation/maintenance without breaking SLAs
• Root-cause performance diagnosis — wait-stats analysis, CPU/memory/I-O bottleneck isolation, tempdb contention, and blocking/deadlock resolution
• Cloud-native platform tuning — hands-on optimization specific to Azure SQL Database, Azure SQL Managed Instance, and AWS RDS for SQL Server: correct service tier/vCore or DTU sizing, storage throughput/IOPS tuning, elastic pool configuration, and working within PaaS resource-governor limits
• Proactive performance baselining — establishing and monitoring baselines so degradation is caught before it becomes a client-facing incident, not just reactive firefighting