Data Sales Specialist, Google Cloud
Skills
- Enterprise Sales
- Value Selling
- BigQuery
- Apache Spark
- Data Analytics
- AI/ML
- Cloud Infrastructure
- Business Case Development
- Stakeholder Management
- Data Management
About the role
Responsibilities:
Deliver against quota and achieve or exceed strategic business and growth goals, and drive net-new greenfield logos and workloads in existing accounts through proactive campaigns.
Run complex, multi-threaded sales cycles from initial discovery and value hypothesis to Return on Investment (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 Field Sales Representative (FSRs) and Partners to execute joint Data+AI plays, driving platform standardization and co-sell motions.
Present 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.
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:
10 years of experience in a sales role selling data analytics or data management technologies to clients.
Experience positioning and selling streaming solutions, open data lakehouses, and analytics tools (e.g., Apache Iceberg, Delta Lake, Apache Spark) against legacy, proprietary deployment environments.
Experience positioning, selling, or showcasing the commercial value of AI platforms, agent-driven applications, and low-latency, highly scalable operational data services on open data foundations.
Use agentic or AI tools for customer demos and discussions for show don't tell execution.
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