Description

Job Description

1. Engagement Overview

We operate an enterprise BI ecosystem supporting 50% client people

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)

Key Skills

Education

Any Graduate