AI-Driven Tableau Data Architect for Enterprise Analytics

Buyers Edge Platform; New London (CT); On-site; USD 120,000 - 190,000; Full time

Benefits offered by this job

Medical benefits

Dental benefits

Vision benefits

401(k) with match

Life insurance

Job summary

Buyers Edge Platform is seeking a Tableau Data Architect to design scalable, governed Tableau data models for enterprise analytics. You will lead governance, semantic data modeling, and AI-ready architecture across Tableau Cloud, ensuring trusted metrics and high performance for executives and analysts.

The role requires 4+ years in BI/analytics with Tableau expertise, strong SQL (Redshift), and collaboration across data engineering, analytics, and business stakeholders.

Qualifications

• Hands-on BI/Data architecture experience with Tableau Cloud governance and security.
• Experience building AI-ready semantic data models for Tableau Next features.
• Strong SQL skills and data modeling across large scale data environments.

Responsibilities

• Own enterprise data governance within Tableau Cloud and enforce data access controls.
• Design AI-ready data models and certify metrics across the organization.
• Develop optimized semantic layers and centralize data sources for dashboards.
• Collaborate with data engineering and BI to ensure trusted, actionable reporting.

Skills

Tableau Cloud

SQL (Amazon Redshift)

Data modeling

Data governance

Tableau REST API

Metadata API/GraphQL

Python scripting

Tableau Catalog

Tableau Pulse

VizQL Data Service

Tools

Tableau Catalog

Tableau Pulse

Einstein Copilot

VizQL Data Service

Tableau Metadata API

Job description

Buyers Edge Platform is seeking a Tableau Data Architect to design scalable, governed Tableau data models for enterprise analytics. You will lead governance, semantic data modeling, and AI-ready architecture across Tableau Cloud, ensuring trusted metrics and high performance for executives and analysts.

The role requires 4+ years in BI/analytics with Tableau expertise, strong SQL (Redshift), and collaboration across data engineering, analytics, and business stakeholders.