Qualifications:
This is not a report developer or visualization designer role. We require platform infrastructure engineers, distributed systems specialists, and API-first architects to drive extreme scalability, harden data security, and lead the integration of Tableau with Enterprise Generative AI and autonomous agents.
Core Deliverables
• Tableau Studio: Enterprise-wide rollout, lifecycle governance, self-serve onboarding, and creator community adoption.
• Tableau Data Apps: Architecture and deployment of interactive, web-based analytics applications using modern embedding frameworks (Embedding API v3, VizQL Data Service).
• Endor + Tableau (EA): Deep integration with Enterprise Assistant (EA) and autonomous BI agents; providing certified semantic grounding to eliminate LLM hallucinations while preserving dynamic user entitlements.
• MCP Server Enablement: Production Model Context Protocol (MCP) pipelines exposing Tableau schemas, metadata, and query engines to developer and analyst AI workflows.
Required Technical Competencies
• Cluster Scalability & Distributed Engines:
• Multi-node cluster architecture and tuning under heavy peak concurrency.
• Native integration and query performance optimization with modern engines: Trino, StarRocks, and Snowflake.
• Workload optimization: Hyper extract caching, backgrounder scheduling, and query bottleneck analysis.
• Security, Entitlements & Compliance:
• Dynamic Row-Level (RLS) and Column-Level Security (CLS) integrated with LDAP/AD.
• Headless and API security: OAuth, SAML, Personal Access Tokens, and Connected Apps (JWT).
• Cross-border data sovereignty and regulatory isolation (China PIPL).
• APIs & Developer Platform:
• Expert-level REST API, Metadata API (GraphQL), and Embedding API v3.
• VizQL Data Service / Headless Tableau for programmatic data extraction.
• Robust automation scripting in Python or TypeScript/Node.js.
• GenAI, Autonomous Agents & MCP:
• Practical development and deployment of Model Context Protocol (MCP) servers.
• Structuring BI semantic models as machine-readable context for LLMs.
• Enforcing end-user identity and entitlement propagation through AI tool calls.
Candidate Qualifications
• Experience: 812+ years in Enterprise Data Engineering / Systems Architecture, with 5+ years dedicated to enterprise Tableau platform infrastructure and APIs.
• Background: Proven track record in Big Tech, hyperscale SaaS, or Tableau Professional Services.
• Scale: Verifiable experience ope rating clusters supporting >25,000 active users and leading legacy migrations (ThoughtSpot, BusinessObjects, HAWK).
Vendor Technical Pre-Screening Questions
(Candidates must provide written technical responses with resume submission:)
1. AI & MCP: How would you architect an MCP server that lets an AI agent query Tableau data while dynamically passing the user's identity to enforce Row-Level Security (RLS)?
2. Scalability: What caching, pooling, and workbook optimization strategies prevent cluster overload and ensure sub-second response times?
Salary Range: $110,000-$150,000 a year
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