DBA Load Testing

• Deadlock troubleshooting
• Prometheus

This is a highly specialized role requiring deep expertise in database performance engineering, scalability testing, workload analysis, and bottleneck identification within mission-critical transactional systems.

We are seeking top-tier, senior candidates, not generalists. Familiarity with tools such as k6 (preferred), Locust, Gatling, distributed load generation, and modern observability stacks is expected.

The ideal candidate will have extensive experience with MariaDB and MySQL, performance tuning under load, replication optimization, database observability, and database scalability strategies.

• Hands-on Performance & Load Testing experience is mandatory.
• Strong experience with MariaDB and MySQL performance engineering.
• Experience working on high-scale, event-driven transactional platforms.
• Expertise with k6 (preferred), Locust, Gatling, or comparable load-testing frameworks.
• Experience supporting distributed load generation and large-scale performance testing programs.
• Strong familiarity with modern observability stacks including Grafana, Prometheus, Datadog, and Open Telemetry.
• Proven ability to identify, analyze, and remediate complex database performance bottlenecks.
• Experience working in cloud-native environments and collaborating within Performance Engineering teams.
• Must be a senior specialist, not a generalist DBA.

• 7+ years of experience as a Database Administrator with strong focus on database performance engineering.
• Extensive hands-on experience administering and optimizing MariaDB and MySQL environments.
• Proven experience supporting Performance & Load Testing initiatives for high-volume transactional systems.
• Strong expertise with performance testing tools such as k6, Locust, Gatling, or equivalent load testing frameworks.
• Experience supporting distributed load generation and large-scale workload simulations.
• Deep understanding of:
• Query optimization
• Index optimization
• Execution plan analysis
• Database tuning
• Lock contention analysis
• Deadlock troubleshooting
• Replication performance tuning
• Replication-lag analysis
• Experience monitoring and tuning:
• Connection saturation
• IOPS
• CPU utilization
• Memory utilization
• Buffer pool efficiency
• Query latency
• Transaction throughput
• Strong understanding of database scalability strategies including:
• Read replicas
• Schema separation
• Partitioning
• Sharding
• Vertical scaling
• Horizontal scaling
• Experience supporting cloud-native and Kubernetes-based environments.
• Expertise with modern observability platforms including:
• Grafana
• Prometheus
• Datadog
• Open Telemetry
• Database performance monitoring tools
• Strong Linux administration and automation experience.

• Database Performance Engineering.
• Performance testing and benchmarking.
• Capacity planning and scalability analysis.
• Root cause analysis and bottleneck identification.
• Production workload analysis.
• Reliability and resiliency assessment.
• Cross-functional collaboration with Software Engineering, Infrastructure, and Performance Engineering teams.
• Strong communication and stakeholder management skills.
• Technical leadership and mentoring.

• Lead database performance and load testing efforts across large-scale transactional platforms.
• Design, execute, and analyze database-focused performance, load, stress, endurance, and scalability tests.
• Analyze and tune database behavior under heavy workload conditions.
• Optimize SQL queries, indexes, schema design, and database configurations to improve performance.
• Investigate lock contention, deadlocks, slow queries, replication delays, and resource bottlenecks.
• Monitor database saturation metrics including:
• Active connections
• Query throughput
• Disk IOPS
• CPU utilization
• Memory utilization
• Buffer pool efficiency
• Replication health
• Identify database bottlenecks impacting application performance and overall platform scalability.
• Partner with Software, QA, and Infrastructure Engineers to diagnose end-to-end performance issues.
• Provide recommendations for database scaling strategies, including:
• Instance sizing upgrades
• Read replicas
• Schema separation
• Database partitioning
• Sharding approaches
• Configure proactive monitoring, alerting, and observability solutions to ensure database health and performance.
• Support distributed load generation exercises and validate database behavior under production-scale workloads.
• Produce detailed…