Google

Runs Search and YouTube and builds Gemini AI

Data Cloud Sales Specialist

Account ExecutiveConfirmed live in the last 24 hours

Full-timeSingaporeNo salary listedIn-person

About the Job

Requirements

A bachelor's degree or equivalent practical experience.
10 years of experience with quota-carrying enterprise sales.
5 years of experience leading enterprise data modernization, cloud data warehousing, or data platform migrations.
Experience building business cases through workshops or product demonstrations to business executives.
Experience developing partnerships with technical stakeholders, such as enterprise architects, data engineers, and data scientists.
Experience positioning and selling technical solutions in data management, analytics, infrastructure, or artificial intelligence.

Responsibilities

Deliver strategic business outcomes and growth goals while achieving or exceeding the sales quota.
Drive net-new greenfield logos and new workloads in existing accounts through proactive engagement.
Run complex, multi-threaded sales cycles from initial discovery and value hypothesis to return-on-investment business case creation and commercial close.
Engage C-level, lines of business, and information technology teams through value-selling, tying modern data and artificial intelligence capabilities to quantified business outcomes.
Align cross-functionally with field sales representatives and partners to execute joint data and artificial intelligence sales plays, scale success and Google Cloud Platform data adoption, drive platform standardization, and execute co-sell motions.
Whiteboard end-to-end modern data architectures, including BigQuery, Spark, Spanner, and AlloyDB, to demonstrate how unified data foundations power optimized price-performance and hallucination-free artificial intelligence agents.

Desired Qualifications

Experience positioning modern cloud data platforms, lakehouses, real-time streaming, or generative artificial intelligence platforms against legacy or other proprietary enterprise systems.
Experience working with global system integrators, hyperscalers, or independent software vendors to co-sell and accelerate pipeline.
Experience closing large-scale data and artificial intelligence transformation agreements within regulated or high-growth enterprise verticals such as financial services, healthcare/life sciences, retail, or manufacturing.
Practical understanding of how modern cloud architectures, data governance (such as cataloging, lineage, and compliance), and clean data estates enable artificial intelligence and real-time analytics.

Deliver strategic business outcomes and growth goals while achieving or exceeding your sales quota. Drive net-new greenfield logos and new workloads in existing accounts through proactive engagement.
Run complex, multi-threaded sales cycles from initial discovery and value hypothesis to ROI business case creation and commercial close.
Engage C-level, Lines of Business and IT teams, 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 sales plays to scale success and GCP data adoption, driving platform standardization and co-sell motions.
Whiteboard end-to-end modern data architectures including but not limited to BigQuery, Spark, Spanner and AlloyDB to demonstrate how unified data foundations power optimized -price-performance, hallucination-free AI agents.

Minimum qualifications:

Bachelor's degree or equivalent practical experience.
10 years of experience with quota-carrying enterprise sales.
5 years of experience leading enterprise data modernization, cloud data warehousing (e.g., Online Analytical Processing (OLAP)), or data platform migrations.
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:

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 agreements 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.

Bachelor's degree or equivalent practical experience.
10 years of experience with quota-carrying enterprise sales.
5 years of experience leading enterprise data modernization, cloud data warehousing (e.g., Online Analytical Processing (OLAP)), or data platform migrations.
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.

About the Company

Google

Runs Search and YouTube and builds Gemini AI

Google runs the world's most used search engine and free services such as YouTube, Android, and Gmail, and it builds the Gemini AI models that work inside them. In 2017, its researchers invented the transformer, the neural network design behind ChatGPT and most other AI chatbots. People use these services without paying, and Google earns most of its money from ads placed beside search results and YouTube videos. Businesses rent computing power and Gemini models through Google Cloud, and Google also sells subscriptions and Pixel phones. Larry Page and Sergey Brin founded Google in 1998 as Stanford PhD students; it is based in Mountain View, California, United States, and is the main business of parent company Alphabet.

Company size: 10,001+
Company stage: IPO
Headquarters: Mountain View, CA
Founded: 1998

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