Google Hiring: Data Analytics Sales Specialist 2026:-
Google is hiring experienced professionals for the position of Data Analytics Sales Specialist – Google Cloud in Mumbai, Maharashtra, India. Candidates with extensive enterprise sales experience and expertise in Data Analytics, Cloud Computing, AI/ML and technical solution selling can explore this opportunity.
| Company: | |
| Job Role: | Data Analytics Sales Specialist |
| Department: | Enterprise Sales / Google Cloud |
| Experience: | 10 Years |
| Salary: | As per company Standards |
| Application Deadline: | ASAP |
Role Overview:-
As a Data Analytics Sales Specialist – Google Cloud, you will drive enterprise sales and business growth for Google Cloud’s Data and AI solutions.
The role focuses on acquiring new enterprise customers, identifying business opportunities, developing strategic relationships and positioning Google Cloud’s modern data platforms against traditional enterprise systems.
You will work closely with enterprise sales representatives, customer engineers, technical stakeholders and external partners to develop business opportunities and close large-scale technology transformation deals.
You will also engage with senior business executives, including Chief Data Officers (CDOs), Chief Financial Officers (CFOs) and Chief AI Officers (CAIOs), to understand business challenges and demonstrate the value of Google Cloud solutions.
Educational Requirements:-
- Bachelor’s Degree in any relevant discipline.
- Equivalent practical experience may also be considered.
- Strong professional experience in enterprise sales and technical solution selling.
Relevant Educational Background:
- B.E. / B.Tech – Computer Science / Information Technology.
- B.Sc. – Computer Science / Mathematics / Statistics.
- BCA – Computer Applications.
- BBA / MBA – Business Administration.
- Other relevant technical or business qualifications.
Key Skills:-
1. Technical Skills
- Google Cloud Platform (GCP)
- BigQuery
- Knowledge Catalog
- Borderless Lakehouse
- Google Cloud Spanner
- AlloyDB
- Apache Spark
- Cloud Data Analytics
- Data Management
- Data Warehousing
- Real-Time Data Streaming
- Generative AI (GenAI)
- Artificial Intelligence (AI)
- Machine Learning (ML)
- Cloud Infrastructure
- Data Governance
- Modern Cloud Architecture
- Enterprise Data Platforms
- AI Agent Solutions
2. Enterprise Sales & Functional Skills
- Enterprise Sales
- Quota-Based Sales
- Technical Solution Selling
- Business Development
- Strategic Account Management
- Consultative Selling
- Value-Based Selling
- Lead Generation
- New Customer Acquisition
- Pipeline Development
- Revenue Growth
- Sales Negotiation
- Business Case Development
- Return on Investment (ROI) Analysis
- Total Cost of Ownership (TCO) Analysis
- Partner Relationship Management
- Co-Selling Strategies
- Enterprise Customer Engagement
3. Cloud & AI Domain Skills
- Cloud Data Modernization
- Data Platform Transformation
- Lakehouse Architecture
- Real-Time Analytics
- Data Integration
- Data Cataloging
- Data Lineage
- Data Compliance
- AI/ML Platform Positioning
- Generative AI Solutions
- AI-Ready Data Infrastructure
- Enterprise Data Governance
4. Soft Skills
- Excellent verbal and written communication.
- Strong presentation and demonstration skills.
- Executive-level stakeholder management.
- Strategic thinking and business development.
- Negotiation and influencing skills.
- Relationship-building abilities.
- Analytical and problem-solving skills.
- Cross-functional team collaboration.
- Customer engagement and client management.
- Leadership and decision-making abilities.
Roles & Responsibilities:-
1. Enterprise Sales & Business Development
- Achieve or exceed assigned sales quotas and business growth targets.
- Identify new enterprise customers and greenfield business opportunities.
- Develop sales strategies to acquire new customers and expand existing accounts.
- Identify untapped workloads and business opportunities.
- Drive revenue growth through Google Cloud’s Data and AI solutions.
- Build and maintain a strong enterprise sales pipeline.
2. Customer Engagement & Value Selling
- Engage with senior business executives to understand their technology and business requirements.
- Work with Chief Data Officers, Chief Financial Officers, Chief Marketing Officers and Chief AI Officers.
- Understand customer challenges and recommend suitable cloud-based solutions.
- Demonstrate the business value of modernizing data infrastructure on Google Cloud.
- Develop business cases highlighting Return on Investment (ROI) and Total Cost of Ownership (TCO) improvements.
- Conduct customer workshops, product demonstrations and solution presentations.
3. Google Cloud Data & AI Solutions
- Position Google Cloud’s modern data and analytics platforms to enterprise customers.
- Promote solutions including BigQuery, Knowledge Catalog, Borderless Lakehouse, Spanner and AlloyDB.
- Explain how unified data platforms support advanced analytics and AI applications.
- Demonstrate how well-governed data foundations support secure and reliable AI agents.
- Help customers modernize legacy data platforms and adopt cloud-based solutions.
- Guide customers on modern cloud architectures and real-time analytics capabilities.
4. Strategic Partnerships & Collaboration
- Collaborate with Field Sales Representatives (FSRs) to execute joint sales strategies.
- Work with customer engineers and technical teams to develop suitable solutions.
- Build relationships with technical stakeholders, including enterprise architects, data engineers and data scientists.
- Partner with global system integrators, hyperscalers and Independent Software Vendors (ISVs).
- Support co-selling initiatives and joint business development opportunities.
- Strengthen long-term enterprise customer relationships.
5. Business Case & Sales Execution
- Manage complex enterprise sales cycles from initial discovery to commercial closure.
- Identify customer requirements and develop value-based sales proposals.
- Present technical solutions through workshops and product demonstrations.
- Develop ROI and TCO business cases.
- Handle customer objections and support commercial negotiations.
- Drive large-scale Data and AI transformation agreements.
6. Data Modernization & AI Transformation
- Help enterprises transition from legacy data systems to modern cloud platforms.
- Position cloud data platforms, lakehouses and real-time streaming solutions.
- Explain the importance of data governance, cataloging, lineage and compliance.
- Demonstrate how clean and unified data environments support AI and Machine Learning.
- Help customers establish long-term data platform standardization.
About Company:-
Google is a global technology company providing products and services across search, advertising, cloud computing, artificial intelligence, software and digital technologies.
Google helps businesses, developers, educational institutions and government organizations use technology to improve productivity, innovation and business performance.
About Google Cloud:-
Google Cloud provides enterprise-grade cloud computing, data analytics, infrastructure, AI and Machine Learning solutions to organizations worldwide.
Its services help businesses modernize their technology infrastructure, manage large datasets, develop AI applications and accelerate digital transformation.
Google Cloud supports customers across more than 200 countries and territories.
Google Hiring: Data Analytics Sales Specialist 2026 Application Process:-
Apply Link:- Click Here To Apply
Note:- Only the shortlisted candidates will be notified for the further interview process.
