US: $183000 - $265000 (USD) + 20% bonus target + equity + benefits
Learn more about benefits at Google.
Design and manage unified, multi-model database solutions (including relational, key-value, graph, and vector search engines). Deploy MCP servers to expose databases as secure, standardized interfaces for AI agents.
Lead complex database modernizations using migration Agents. Standardize source-to-destination transfers, utilizing tools like the Database Migration Service (DMS).
Shift database SRE to proactive, AI-driven management. Utilize the Gemini-powered database center and the database observability agent to consume real-time telemetry, automate workload simulations, perform root-cause analysis, and apply remediations.
Implement QueryData APIs and database-specific contexts to build conversational analytics experiences, translating natural language business queries into SQL with high accuracy.
Establish security protocols, encryption, and access control policies (IAM) aligned with industry regulations and Google Cloud best practices.
Minimum qualifications
Bachelor's degree in Computer Science, Information Systems, a related technical field, or equivalent experience.
8 years of experience with Google Cloud Databases (e.g., AlloyDB, Cloud SQL, Spanner, Firestore, and Bigtable).
Experience with RDBMS such as PostgreSQL, Oracle, and SQL Server (e.g., engines, schema design, and concurrency).
Experience in application development using Java, Python, build systems, ORMs (e.g., Hibernate), and JDBC.
Experience with IaC and AI, including Terraform provisioning and AI integration via LangChain and LangGraph.
Experience with performance and HA/DR (e.g., diagnosing execution plans, wait states, indexing, connection pooling, replication, automated failover, multi-region DR, and point-in-time recovery).
Preferred qualifications
Master’s degree in Engineering, Computer Science, Business, or a related field.
Certifications: Professional Cloud Database Engineer.
Experience using Gemini analytics and Observability Agents to diagnose plans, resolve contentions, optimize pooling, and benchmark.
Experience managing hybrid/multi-cloud data environments or migrating to Google Cloud.
Knowledge of AI-native database design, combining RDBMS expertise with vector and graph technologies, and tying databases into modern pipelines (e.g., Dataflow, CDC).
Ability to design agent architectures (routing, state management) and integrate databases via MCP Toolbox for secure endpoints.
Bachelor's degree in Computer Science, Information Systems, a related technical field, or equivalent experience.
8 years of experience with Google Cloud Databases (e.g., AlloyDB, Cloud SQL, Spanner, Firestore, and Bigtable).
Experience with RDBMS such as PostgreSQL, Oracle, and SQL Server (e.g., engines, schema design, and concurrency).
Experience in application development using Java, Python, build systems, ORMs (e.g., Hibernate), and JDBC.
Experience with IaC and AI, including Terraform provisioning and AI integration via LangChain and LangGraph.
Experience with performance and HA/DR (e.g., diagnosing execution plans, wait states, indexing, connection pooling, replication, automated failover, multi-region DR, and point-in-time recovery).
