Solutions Architect, Data, Google Cloud

Google LLC
Austin, United States of America
5 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior
Compensation
$ 265K

Job location

Austin, United States of America

Tech stack

Java
Artificial Intelligence
Google BigQuery
Bioinformatics
Cloud Computing
Databases
ETL
Data Migration
Data Warehousing
Python
NoSQL
Open Source Technology
Azure
SQL Databases
Google Cloud Platform
Spark
Generative AI
Information Technology
Data Analytics
Looker Analytics
Data Pipelines

Job description

As a Solutions Architect, you'll work with technical sales, customers and Google Cloud Product and Engineering teams to produce secure and scalable technical solutions and distribute them via multiple channels, including technical white papers, open-source repositories, webinars, videos, blogs, and live presentations. Your passion for technology and solving problems, along with your enthusiasm for working with customers and communication skills, will empower a audience of decision makers to adopt Google Cloud to build what's next for their businesses.

You will work with a variety of customers across industries to help them optimize their business use cases with Google Cloud. You will create technical solution assets to help customers securely deploy these alongside other cloud technologies, and present these solutions to customers, as well as at industry specific events. You will work with Product and Engineering teams that focus on these technologies to identify opportunities to reduce friction and increase adoption.

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.

The US base salary range for this full-time position is $183,000-$265,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more aboutbenefits at Google (https://careers.google.com/benefits/) .

Responsibilities

  • Facilitate technical discussions with customers, partners, and Google Cloud technical sales organizations. Provide subject matter expertise regarding Data Cloud portfolio (Databases, Big Query, and Looker) to effectively promote Google Cloud with customers through technical collateral and external conferences.
  • Support Technical Account Managers and Sales Engineering teams as needed through all phases of customer engagement.
  • Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted for technical and business stakeholders.
  • Provide customer and market feedback to Product and Engineering teams to help shape product direction.

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) .

Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See alsoGoogle's EEO Policy (https://www.google.com/about/careers/applications/eeo/) ,Know your rights: workplace discrimination is illegal (https://careers.google.com/jobs/dist/legal/EEOC_KnowYourRights_10_20.pdf) ,Belonging at Google (https://about.google/belonging/) , andHow we hire (https://careers.google.com/how-we-hire/) .

If you have a need that requires accommodation, please let us know by completing ourAccommodations for Applicants form (https://goo.gl/forms/aBt6Pu71i1kzpLHe2) .

Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.

To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes.

Requirements

Experience owning outcomes and decision making, solving ambiguous problems and influencing stakeholders; deep expertise in domain., * Bachelor's degree in Computer Science, Mathematics, a related technical field, or equivalent practical experience.

  • 7 years of experience with ETL tools, data pipeline orchestration (e.g., Spark), and data warehousing architectures.
  • Experience with SQL, NoSQL, Python, Java, or data modeling techniques.
  • Experience with Google Cloud's Vertex Platform.

Preferred qualifications:

  • Master's degree in Computer Science, related engineering field, or equivalent work experience.
  • Experience architecting and optimizing cloud infrastructure to support a unified Data and AI/ML platform, ensuring high performance, scalability, and readiness for advanced analytics and Generative AI use cases.
  • Experience architecting and implementing data migration and modernization frameworks, managing rapid adoption, ensuring consistency, and enhancing auditability.
  • Technical experience with Database and Data Analytics platform for building and deploying generative AI applications, including expertise with Big Query, Vertex AI, and GCP Database product portfolio.

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