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Confirmed on the employer's own hiring board on Oct 29, 2026. First seen by Alion on Oct 29, 2026. Google scores B on the Alion truth index.

Overview
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Google is an American technology company founded in 1998 by Larry Page and Sergey Brin and now the principal subsidiary of Alphabet, headquartered in Mountain View, California. It operates the world's dominant search engine and the advertising system built around it, along with YouTube, Android, Chrome, Gmail, Maps, Workspace and Google Cloud, reaching billions of users across nearly every internet-connected market. The company designs its own silicon in the Tensor Processing Unit line, develops the Gemini foundation models through Google DeepMind, and derives most of its revenue from advertising while cloud has become its fastest growing segment.

About the job

As an 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 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 are 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 Data Cloud suite (BigQuery, Knowledge Catalog, Borderless Lakehouse, Spanner, AlloyDB) as the premium data intelligence platform for AI. You will present demonstrations that showcase how unified, well-governed data foundations power secure, hallucination-free AI agents and real-time experiences.

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 strategic business and growth goals. Drive 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.
  • Whiteboard modern architectures (BigQuery, Spark, Spanner, AlloyDB) to demonstrate how unified data foundations power high-performance, hallucination-free AI agents.

Qualifications

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.
  • Ability to communicate in Mandarin and English fluently to manage stakeholder relationships.

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 agreements within specific regulated or high-growth enterprise verticals (e.g., Financial Services, Healthcare/Life Sciences, Retail, or Manufacturing).
  • Understanding of how modern cloud architectures, data governance (e.g., cataloging, lineage, compliance), and clean data estates enable AI and real-time analytics.
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