New to the title? A Solution Engineer (sometimes called a Pre-Sales Engineer or Sales Consultant) gathers business requirements, shapes the technical sales strategy, and demonstrates solutions that deliver business value, building customer confidence and clearing technical objections along the way. Increasingly, SEs also help customers adopt and get full value from what they’ve bought.
Core Responsibilities & Scope
Win Analytics business with Sales: Partner with Account Executives to understand each customer’s goals, manage several engagements at once across ANZ, and build trusted relationships with business leaders, analysts, data architects and data engineers.
Lead discovery and demos: Run discovery sessions and workshops, then build prototypes and customised demos that prove business value. Show how customers can define metrics and business rules once and reuse them everywhere, and how Tableau Semantics, Tableau Knowledge and Tableau Next (with Data 360 and Agentforce) fit their data stack.
Showcase AI and design AI-ready architectures: Demo Tableau Agent and natural-language analytics in Tableau Studio, and show how Tableau MCP (Model Context Protocol) connects trusted data to assistants such as Slack, Claude, ChatGPT and Microsoft Copilot. Build generative AI and governed semantics into every customer architecture from the start.
Support bids, enable the team and represent Tableau: Contribute technical responses to RFPs, RFIs and RFTs, share knowledge with Solution Engineering and adjacent teams, feed customer insights back to Product, and represent Tableau at customer events and Tableau User Groups.
Minimum Requirements
Experience: 3+ years in technical pre-sales, consulting, customer success, analytics or data roles, plus a relevant degree (Computer Science, Software Engineering, Information Systems or similar)
BI and data expertise: Hands-on experience with Tableau, CRM Analytics or similar tools (Power BI, Looker), plus familiarity with data modelling, semantic layers, and how data moves from warehouses, lakes and lakehouses through ETL/ELT pipelines into analytics-ready models.
AI fluency: Working knowledge of generative AI, including LLMs, prompt design, RAG and AI agents, and how they apply to analytics. You understand how MCP servers connect AI assistants to enterprise data and tools.
Communication and sales instinct: You present with confidence, in person and online, to audiences from analysts to executives. You can explain business value, position products, handle technical objections, and manage multiple sales cycles in parallel.
How you stand out
Experience with other cloud data platforms (Snowflake, Databricks, BigQuery), data prep tools (Informatica or similar), or semantic and metrics layers (Tableau Semantics, Published Data Sources, dbt)
Experience with Data 360 or Agentforce, or with setting up MCP servers to connect AI assistants to enterprise data
Salesforce certifications (Tableau Consultant, Tableau Desktop Specialist, CRM Analytics, Administrator), or Salesforce power-user or admin experience
A track record of building demos or proofs of concept, plus published content or community involvement such as blogs, talks or Tableau User Group activity
LI-Y
Unleash Your Potential
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