Principal Data Cloud Solution Engineer

at  Salesforce

To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts.
Job Category
Sales
Job Details

ESSENTIAL REQUIREMENTS

• Experience in customer-facing solutioning for Data, Analytics, AI (ML/RAG) and CRM
• Full-stack technical qualifications (CRM, Data Architecture, AI/ML) combined with experience owning technical relationships with C-Level executives
• Experience integrating complex data architectures to drive business value for customers
• Experience in 1 or more Hyperscale Data providers (ex. AWS, Azure, GCP)
• Skilled at guiding impactful discovery conversations to unveil multifaceted client needs and objectives
• Experience driving customer success in large, complex selling organizations
• Persuasive verbal, written, presentation and interpersonal communication skills that inspire change in large organizations
• Fluent in English (+fluent in Nordic language is a pre)

PREFERRED REQUIREMENTS

• Understanding market trends in consumption selling business and experience in driving consumption through value use cases
• Hands-on expertise in modern cloud data platforms (Snowflake, Databricks, Big Query, RedShift), data analytics tools (Tableau, Looker, Power BI), data programming models (DataFrames, pandas), and AI
• AI: Data Engineering, machine learning, Vector Databases & RAG, MLOps (a plus: Agentic AI and Agents)
• Technical knowledge of the Salesforce platform
• Experience will be evaluated based on alignment to the core competencies for the role (e.g. extracurricular leadership roles, military experience, volunteer work, etc.)
  Accommodations
  If you require assistance due to a disability applying for open positions please submit a request via this Accommodations Request Form .
  Posting Statement
  At Salesforce we believe that the business of business is to improve the state of our world. Each of us has a responsibility to drive Equality in our communities and workplaces. We are committed to creating a workforce that reflects society through inclusive programs and initiatives such as equal pay, employee resource groups, inclusive benefits, and more. Learn more about Equality at www.equality.com and explore our company benefits at www.salesforcebenefits.com .
  Salesforce is an Equal Employment Opportunity and Affirmative Action Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender perception or identity, national origin, age, marital status, protected veteran status, or disability status. Salesforce does not accept unsolicited headhunter and agency resumes. Salesforce will not pay any third-party agency or company that does not have a signed agreement with Salesforce .
  Salesforce welcomes all.

• Arrange and conduct in-person & web-based meetings to drive the entire opportunity lifecycle from technical discovery to technical close
• Collaborate strategically with Account Executives across the customer base and the sales organization to prioritize and develop Industry-specific use cases grounded in consistent architectures that have proven repeatability with customers
• Implement programs to efficiently scale technical evaluation of Salesforce Data Cloud
• Collaborate with Salesforce product teams to deeply understand Salesforce solutions and roadmap, and advocate for key features needed for success across the Industry/Territory via Voice of the Customer feedback
• Develop scalable, deployable, reusable, and relevant field enablement technical assets that drive differentiated business outcomes in order to accelerate adoption across customers, partners, and sales teams
• Partner with Product Marketing to advise messaging and sales plays across all of Salesforce
• Deliver the overall Salesforce point-of-view for data strategy aligned to industry-specific use cases
• Experience in articulating Data & AI ROI value to Business & getting the IT buy in
• Industry domain experience relevant to Data architecture approaches and knowledge in mapping business capabilities to technical capabilities
• Aware of latest trends in industry including Lakehouses, data governance, LLMs, Agents