Solutions Architect, Data Cloud

This opportunity is open for applications with preferred working locations in Chicago, IL, USA; Boulder, CO, USA; Austin, TX, USA; or Miami, FL, USA.

About the role

As a Technical Solutions Consultant and Solutions Architect for Data Cloud, you will act as a technical expert for Google Cloud’s Customer Engineering and field teams. You’ll lead cross-functional teams in Engineering, Sales, and Product Management to leverage emerging technologies for external clients and partners. Your role involves designing, prototyping, and publishing production-ready Data Cloud assets, establishing technical ownership over complex data domains, and collaborating with Product and Engineering to drive innovation. You will bridge Customer Engineering, Product, and Engineering to accelerate deployment and help customers build next-generation solutions at scale.

Responsibilities

• Design, prototype, and publish production-ready Data Cloud assets, reference architectures, and technical accelerators to scale field enablement.
• Establish end-to-end technical ownership over complex data domain spaces, guiding core architectural decisions across databases, analytics, business intelligence, and GenAI.
• Architect and scale high-impact technical assets (demos, reference architectures, and guides) showcasing Google Cloud’s data capabilities to address customer challenges.
• Collaborate closely with Product and Engineering to inject real-world insights into the product roadmap and drive continuous innovation.
• Build tools, automate products, and oversee the technical execution and business operations of Google’s partnerships.
• Develop product strategy, prioritize projects, and allocate resources to align with business and partner needs.
• Address complex customer issues, build secure and scalable reference implementations, and advocate for Google Cloud technologies.
• Design technical architectures spanning on-prem and cloud solutions, incorporating AI and novelty adjustments while considering cost, security, privacy, regulatory requirements, data governance, and reliability.

Requirements

• Bachelor's degree in Computer Science, Mathematics, a related technical field, or equivalent practical experience.
• 10 years of experience with ETL tools, data pipeline orchestration (e.g., Spark), and data warehousing architectures.
• 2 years of experience with Google Cloud’s Vertex Platform.
• Experience with SQL, NoSQL, Python, Java, or data modeling techniques.

Preferred Qualifications

• Master's degree in Computer Science, related engineering field, or equivalent practical experience.
• 15 years of experience writing bespoke code, building custom tooling, or contributing to core codebases to resolve critical technical issues.
• Experience developing, deploying, and optimizing data architecture deployments and generative AI agents, particularly conversational AI on enterprise platforms.
• Expertise in CI/CD pipelines, agent performance tuning, and production readiness for cloud-based data applications.
• Proven track record of creating reusable tools, technical accelerators, and documentation to scale engineering enablement.

Pay

Individual pay is determined by job-related skills, experience, and relevant education or training. US-based roles: $233,000 - $324,000 (USD) plus 25% bonus target, equity, and benefits.

Benefits

Learn more about benefits at Google.