Why This Role Stands Out
This role offers a unique opportunity to shape the future of enterprise BI by integrating Tableau with cutting-edge AI technologies, providing significant career growth. You'll thrive here if you are a seasoned platform infrastructure engineer or distributed systems specialist passionate about scalability, data security, and innovative AI integrations. Apply today to lead impactful projects within a renowned organization!
Quick Overview
Job Description
Position: Senior / Principal Enterprise Tableau Platform & AI Integration Consultant
Location: Sunnyvale, CA (Onsite)
Project Type: Full-Time
1. Engagement Overview
We operate an enterprise BI ecosystem supporting 50% Apple people.
Note: 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.
2. Core FY27 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.
3. 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.
4. Candidate Qualifications
· Experience: 8–12+ 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 operating clusters supporting >25,000 active users and leading legacy migrations (ThoughtSpot, BusinessObjects, HAWK).
5. 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?
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