Principal Enterprise Tableau Platform & AI Integration Consultant

Tata Consultancy Services; Sunnyvale (CA); On-site; USD 110,000 - 150,000; Full time

Job summary

Tata Consultancy Services in Sunnyvale, CA seeks platform infrastructure engineers and API-focused architects to scale Tableau across the enterprise, secure data access, and integrate with Enterprise Generative AI and autonomous BI agents. Responsibilities include Studio rollout, Data Apps deployment, and MCP-enabled AI workflows.

Ideal candidates have 8–12+ years in enterprise data engineering or architecture, with 5+ years on Tableau infrastructure and strong API experience.

Qualifications

• Experience: 8–12+ years in Enterprise Data Engineering / Systems Architecture.
• 5+ years in enterprise Tableau platform infrastructure and APIs.
• Track record in hyperscale environments and major migrations.

Responsibilities

• Lead Tableau Studio rollout, governance, onboarding, and creator community adoption.
• Architect and deploy Tableau Data Apps using embedding frameworks.
• Integrate Endor + Tableau with EA and autonomous BI agents for secure, scalable analytics.
• Enable MCP pipelines exposing Tableau schemas and engines to AI workflows.

Skills

Cluster scalability

Security & entitlements

APIs & developer platform

GenAI & MCP

Automation scripting

Tools

Trino

StarRocks

Snowflake

REST API

GraphQL Metadata API

Embedding API v3

Python

TypeScript/Node.js

Job description

Job Description

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.

• 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.

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: 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 ope rating clusters supporting >25,000 active users and leading legacy migrations (ThoughtSpot, BusinessObjects, HAWK).

Vendor Technical Pre-Screening Questions

• 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)?
• 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