Pay
Higher than most similar jobs
$183K–$265K against $127K–$190K, the middle half of what similar US postings state.
From 2,133 postings in the last year. Stated ranges, not salaries paid.
Chicago, IL
Actively hiring, first seen by us 5 days agoIndividual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $183000 - $265000 (USD) + 20% bonus target + equity + benefits Learn more aboutbenefits at Google (https://www.google.com/about/careers/applications/benefits/) .Read the full posting
Design and manage multi-model database solutions and expose them to AI agents via MCP servers
Lead complex database migrations using migration agents and Database Migration Service
Run database SRE with Gemini-powered tools, root-cause analysis, and remediation
Build conversational analytics that translate natural language queries into SQL
Set up security, encryption, and IAM access controls aligned with best practices
Design and manage unified, multi-model database solutions (including relational, key-value, graph, and vector search engines).
Lead complex database modernizations using migration Agents.
Shift database SRE to proactive, AI-driven management.
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).
**Preferred qualifications:** + Master’s degree in Engineering, Computer Science, Business, or a related field. + Certifications: Professional Cloud Database Engineer.
Actively hiringFirst seen by us 5 days ago, still listed, and not a repost of an earlier posting.
We found this posting on the National Labor Exchange. These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Higher than most similar jobs
$183K–$265K against $127K–$190K, the middle half of what similar US postings state.
From 2,133 postings in the last year. Stated ranges, not salaries paid.
Day 5
Early. Similar jobs usually come down between day 6 and day 54.
At Google, jobs usually come down by about day 3.
From 10,948 similar postings that came down, and 486 of Google’s. Coming down is not always a hire.
287 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
+ 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.
+ 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).
+ 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.
+ 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.
+ 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).
Agentic Data Cloud Database Engineer, Google Cloud Share Agentic Data Cloud Database Engineer, Google Cloud
Agentic Data Cloud Database Engineer, Google Cloud Share Agentic Data Cloud Database Engineer, Google Cloud _corporate_fare_ Google _place_ Addison, TX, USA; Austin, TX, USA; +3 more; +2 more
Experience owning outcomes and decision making, solving ambiguous problems and influencing stakeholders; deep expertise in domain. Share Agentic Data Cloud Database Engineer, Google Cloud _info_outline_
+ 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).
**About the job** The Google Cloud Consulting Professional Services team guides customers through the moments that matter most in their cloud journey to help businesses thrive. We help customers transform and evolve their business through the use of Google’s global network, web-scale data centers, and software infrastructure. As part of an innovative team in this rapidly growing business, you will help shape the future of businesses of all sizes and use technology to connect with customers, employees, and partners. The Agentic Data Cloud Databases Engineer guides customers through designing, migrating, and optimizing intelligent, multi-model database infrastructure built for the agentic era. You will work closely with enterprise customers to architect scalable, always-on transactional databases that serve as the contextual "brain" and real-time execution engine for AI agents. By leveraging automated onboarding, testing, migration, and observability database agents, you will de-risk the customer modernization journey and deliver paved, secure paths to enterprise-wide AI innovation.
The Agentic Data Cloud Databases Engineer guides customers through designing, migrating, and optimizing intelligent, multi-model database infrastructure built for the agentic era. You will work closely with enterprise customers to architect scalable, always-on transactional databases that serve as the contextual "brain" and real-time execution engine for AI agents. By leveraging automated onboarding, testing, migration, and observability database agents, you will de-risk the customer modernization journey and deliver paved, secure paths to enterprise-wide AI innovation. Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems. Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
+ 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. Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google'sApplicant and Candidate Privacy Policy (./privacy-policy) .
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Yes. We’ve followed 3 other Agentic Data Cloud Database Engineer, Google Cloud jobs there since October 2026. All 3 are still up.
Large employers often post one title for several teams, so these can be separate openings.
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
Selected passages from the saved posting. Check the full description for conditions and exceptions.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $183000 - $265000 (USD) + 20% bonus target + equity + benefits Learn more aboutbenefits at Google (https://www.google.com/about/careers/applications/benefits/) .
Chicago, IL
+ 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).
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