Senior Site Reliability Engineer
About the role
What you'll be doing
- Design and operate highly available database clusters (MySQL, MSSQL, Oracle) with automated replication, failover, point-in-time recovery, and disaster-recovery strategies at enterprise scale.
- Drive database performance engineering — own query optimization, indexing strategies, connection pooling, lock-contention analysis, and storage-engine tuning for production systems handling millions of transactions.
- Build self-service database lifecycle automation — from one-click cluster provisioning and schema migrations to zero-downtime upgrades, blue-green deployments, and automated capacity scaling.
- Bridge relational and AI-native data infrastructure — extend traditional database expertise into vector search, GPU-accelerated query engines, and hybrid data platforms that serve both classic workloads and AI applications.
- Compose and build software platforms that transform legacy database systems into modern and scalable architectures.
- Run vector & graph database services and query engines to handle AI/ML data workloads with ultra-low latency.
- Build automation frameworks for provisioning, schema evolution, scaling, and failover integrated directly into CI/CD workflows.
- Build developer-focused tooling for monitoring, profiling, and debugging database performance in real time.
- Contribute to architecture, coding standards, and guidelines for long-term platform evolution.
- Participate in on-call rotations to ensure flawless operation of critical database services.
What we need to see
- BS, MS, or PhD in Computer Science, Engineering, or a related field—or equivalent experience.
- 8+ years of Database engineering experience with deep expertise in database systems or distributed data platforms
- Deep hands-on expertise with one or more major relational database engines (like Oracle, MySQL, MSSQL) — including replication topologies, backup/restore strategies, and high-availability architecture.
- Proven background in query optimization, data partitioning, and large-scale performance tuning.
- Experience building or operating managed database services or internal Database-as-a-Service platforms — automating provisioning, monitoring, patching, and failover for database fleets at scale.
- Strong programming skills in Python, Go, with a track record of building production-grade systems.
- Demonstrable experience crafting high-performance, high-availability relational database services.
- Experience with container orchestration (Kubernetes) and cloud-native database deployment patterns.
- Hands-on experience establishing DevOps guidelines, e.g., CI/CD, monitoring, alerting, SLAs, capacity forecasting, etc.
Ways to stand out from the crowd
- Strong Kubernetes/Infrastructure as code and coding experience in addition to core DBA skills.
- Expertise in hybrid/multi-region database replication strategies for low-latency AI workloads.
- Demonstrable understanding of observability and performance profiling tools for complex data systems.
- You’ve built an internal Database-as-a-Service offering — engineers request a cluster and get a production-ready, fully monitored, backed-up database without filing a ticket.
- Hands-on experience with database migration tooling, schema evolution pipelines, and zero-downtime upgrade strategies across heterogeneous database engines
NVIDIA is committed to encouraging a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/
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Skills
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