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About the role
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. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- Bachelor's degree or equivalent practical experience
- 10 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
More about this role
- 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 Line of 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 (e.g., BigQuery, Spark, Spanner, AlloyDB) to demonstrate how unified data foundations power high-performance, hallucination-free AI agents.
- Bachelor's degree or equivalent practical experience.
- 10 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...
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