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TC
Tata Consultancy Services Limited
Principal Enterprise Tableau Platform & AI Integration Consultant
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Job Description
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 DeliverablesTableau 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 CompetenciesCluster 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