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Salary
$109k – $111k per year
Location
In office (Stockholm)

Confirmed on the employer's own hiring board on Oct 20, 2026. First seen by Alion on Oct 19, 2026. Google scores B on the Alion truth index.

Overview
Company
Impact
Profile match
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 the Agentic Data Cloud Sales Specialists team, we work together with Field Sales Representatives (Account Managers), Customer Engineers, and our Partners to help our customers modernize their operational and analytical data foundations on GCP. We enable them to transition to modern, unified cloud architectures that position data as the absolute foundation for AI success and power next-generation AI and intelligent applications.

As a master of complex lakehouse solutions, data governance, and AI, you are the exact sales expert we need to translate technical capabilities into high-impact business outcomes.

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.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

Sweden: kr1080000 - kr1100000 (SEK) + 100% bonus target + equity + benefits

Learn more about benefits at Google.

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 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 & 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).
  • Ability to communicate in English and Swedish fluently to manage client relationships in the region.

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 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.
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