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Data Sales Specialist, Google Cloud

Google
Bengaluru, IND
Senior · 10+ years experience
Onsite
Discovered 3 days ago
delta-lakeicebergspark

Full Job Posting

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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