Data Analytics Sales Specialist, Google Cloud

About the job

The Google Cloud Platform team helps customers transform and build what's next for their business — all with technology built in the cloud. Our products are developed for security, reliability and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping our customers — developers, small and large businesses, educational institutions and government agencies — see the benefits of our technology come to life. As part of an entrepreneurial team in this rapidly growing business, you will play a key role in understanding the needs of our customers and help shape the future of businesses of all sizes use technology to connect with customers, employees and partners.

As an Agentic Data Cloud Sales Specialist, you will be at the forefront of driving Google Cloud's most critical data and AI growth. In this role, you will drive growth by securing net-new greenfield logos and identify untapped, uncommitted workloads. You will partner with Field Sales Representatives, Customer Engineers, and Partners to execute joint Data+AI plays that establish long-term data platform standardization.

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.

Responsibilities

• Deliver against quota and achieve or exceed  business and growth goals. Drive net-new greenfield logos and workloads in existing accounts through proactive campaigns.
  
• Run complex, multi-threaded business cycles from initial discovery and value hypothesis to ROI business case creation and commercial close.
  
• Engage business leaders, Chief Data Officer, Chief Financial Officer, Chief Marketing Officer, Chief AI Officer, through value-selling, tying modern Data and AI capabilities to quantified business outcomes.
  
• Align cross-functionally with FSRs and Partners to execute joint Data+AI plays, driving platform standardization and co-sell motions.
  
• Illustrate modern architectures (BigQuery, Spark, Spanner, AlloyDB) to demonstrate how unified data foundations power high-performance, hallucination-free AI agents.
  

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
  
• 7 years of quota-carrying enterprise sales experience.
• Experience building business cases through workshops or product demos to business executives.
• Experience developing partnerships with technical stakeholders (e.g., Enterprise Architects, Data Engineers, Data Scientists).
• Experience positioning and selling technical solutions in data management, analytics, infrastructure, or AI/ML.

Preferred qualifications:

• Experience positioning modern cloud data platforms, lakehouses, real-time streaming, or GenAI platforms against legacy or other proprietary enterprise systems.
• Experience working with Global System Integrators, hyperscalers, or ISVs to co-sell and accelerate pipeline.
  
• Experience closing large-scale data and AI transformation deals within specific regulated or high-growth enterprise verticals (e.g., Financial Services, Healthcare/Life Sciences, Retail, or Manufacturing).
  
• Practical understanding of how modern cloud architectures, data governance (e.g., cataloging, lineage, compliance), and clean data estates enable AI and real-time analytics.
  

• Bachelor's degree or equivalent practical experience.
  
• 7 years of quota-carrying enterprise sales experience.
• Experience building business cases through workshops or product demos to business executives.
• Experience developing partnerships with technical stakeholders (e.g., Enterprise Architects, Data Engineers, Data Scientists).
• Experience positioning and selling technical solutions in data management, analytics, infrastructure, or AI/ML.