Agentic Data Cloud Database Engineer, Google Cloud

Google•Kirkland, WA

2d•$183,000 - $265,000

About The Position

The Google Cloud Consulting Professional Services team guides customers through significant moments in their cloud journey, helping businesses transform through Google’s global network, data centers, and software infrastructure. The Agentic Data Cloud Database Engineer guides customers in designing, migrating, and optimizing intelligent, multi-model database infrastructure for the agentic era. The role works closely with enterprise customers to architect scalable, always-on transactional databases that serve as contextual resources and real-time execution engines for AI agents. It uses automated database agents for onboarding, testing, migration, and observability to reduce risk in customer modernization and provide secure paths to enterprise-wide AI innovation.

Requirements

Bachelor’s degree in Computer Science, Information Systems, a related technical field, or equivalent experience.
8 years of experience with Google Cloud Databases, such as AlloyDB, Cloud SQL, Spanner, Firestore, and Bigtable.
Experience with RDBMS such as PostgreSQL, Oracle, and SQL Server, including engines, schema design, and concurrency.
Experience in application development using Java, Python, build systems, ORMs such as Hibernate, and JDBC.
Experience with IaC and AI, including Terraform provisioning and AI integration via LangChain and LangGraph.
Experience with performance and high availability/disaster recovery, including diagnosing execution plans and wait states, indexing, connection pooling, replication, automated failover, multi-region disaster recovery, and point-in-time recovery.

Nice To Haves

Master’s degree in Engineering, Computer Science, Business, or a related field.
Professional Cloud Database Engineer certification.
Experience using Gemini analytics and Observability Agents to diagnose plans, resolve contention, optimize pooling, and benchmark.
Experience managing hybrid or multi-cloud data environments or migrating to Google Cloud.
Knowledge of AI-native database design combining RDBMS expertise with vector and graph technologies, and integrating databases into modern pipelines such as Dataflow and CDC.
Ability to design agent architectures, including routing and state management, and integrate databases via MCP Toolbox for secure endpoints.

Responsibilities

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 and standardize source-to-destination transfers with tools such as Database Migration Service (DMS).
Advance database SRE through proactive, AI-driven management, using the Gemini-powered database center and 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 that translate 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.