Job Description

Minimum qualifications

• Bachelor's degree or equivalent practical experience.
• 10 years of experience in quota-carrying enterprise sales.
• 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 Japanese fluently to manage stakeholder relationships.

Preferred qualifications

• Experience positioning modern cloud data platforms, lakehouses, real-time streaming, or Generative AI (GenAI) platforms against legacy or other proprietary enterprise systems.
• Experience working with Global System Integrators, hyperscalers, or Independent Software Vendors (ISVs) to co-sell and accelerate pipeline.
• Experience closing large-scale data and AI transformation deals within specific regulated or high-growth enterprise verticals (e.g., Financial Services, Healthcare/Life Sciences, Retail, or Manufacturing).
• Practical understanding of how modern cloud architectures, data governance (e.g., cataloging, lineage, compliance), and clean data estates enable AI and real-time analytics.

About the job

As an Agentic Data Cloud Sales Specialists team, we work together with Field Sales Representatives (e.g., Account Managers), Customer Engineers, and our Partners to help our customers modernize their operational and investigative data foundations on Google Cloud Platform (GCP). We enable them to transition to modern, unified cloud architectures that position Data as the absolute foundation for Artificial Intelligence (AI) success and power next-generation AI and intelligent applications.

In this role, you will translate technical capabilities into high-impact business outcomes. You will be at the forefront of driving Google Cloud's most critical data and AI growth. 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 and AI plays that establish long-term data platform standardization. You will engage with line-of-business (LoB) leaders, Chief Data Officer (CDO), Chief Artificial Intelligence Officer (CAIO), and Chief Financial Officer (CFO) to discover critical pain points, build business cases (e.g., Return on Investment/Total Cost of Ownership (ROI/TCO) reduction), and demonstrate the quantifiable business value of modernizing data estates on GCP. You will guide technical stakeholders and position Google Cloud's Agentic Data Cloud suite (e.g., 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.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 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 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 Representatives (FSRs) and Partners to execute joint Data and AI plays, driving platform standardization and co-sell motions.
• Whiteboard modern architectures (e.g., BigQuery, Spark, Spanner, AlloyDB) to demonstrate how unified data foundations power high-performance, hallucination-free AI agents.