Agentic Data Cloud Sales Specialist III, Google Cloud
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Key details
- Salary
- $138K–$200K/yr
- Location
- San Francisco, CA, United States
- Work style
- Onsite
- Level
- Senior
- Experience
- 10–13 yrs
- Function
- Sales & Solutions
- Focus area
- other
- Posted
- 23h ago
Skills
ai agentsai/mlbigquerycloud architecturedata governanceenterprise salesgcpgenerative ailakehouseproduct demonstrationsspark
About the role
About the job
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.You will be a master of value-selling. You will engage with line-of-business (LoB) leaders, CDO, CAIO, and CFO to discover critical pain points, build robust business cases (ROI/TCO reduction), and demonstrate the quantifiable business value of modernizing data estates on GCP.
Additionally, you will guide technical stakeholders and position Google Cloud's Agentic Data Cloud suite (BigQuery, Knowledge Catalog, Borderless Lakehouse, Spanner, AlloyDB) as the premium data intelligence platform for AI. You will present demos that showcase how unified, well-governed data foundations power secure, hallucination-free AI agents and real-time experiences.
US: $138000 - $200000 (USD) + 100% bonus target + equity + benefits
Learn more about benefits at Google.
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 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.
Minimum qualifications:
- 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.
Preferred qualifications:
- Experience positioning modern cloud data platforms, lakehouses, real-time streaming, or GenAI platforms against legacy or other proprietary enterprise systems.
- Experience closing data and AI transformation deals within specific regulated or high-growth enterprise verticals (e.g., Financial Services, Healthcare/Life Sciences, Retail, or Manufacturing).
- Experience working with Global System Integrators, hyperscalers, or Independent Software Vendor (ISVs) to co-sell and accelerate pipeline.
- 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.
- 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.
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