Tableau Data Architect
About the role
We’re seeking a Tableau Data Architect to design and optimize the data architecture that powers our enterprise analytics ecosystem. This role is responsible for architecting scalable, governed, and high-performing Tableau data models that enable actionable insights across our business.
Responsibilities
Own the enterprise data governance framework within Tableau Cloud, including data source certification workflows, Tableau Catalog configuration (lineage tracking, data quality warnings, sensitivity labels), metric governance via Tableau Pulse, and enforcement of naming conventions, access controls, and content promotion policies.
Leverage the Platform Data API to build automated audit trails, activity monitoring pipelines, and compliance dashboards for ongoing governance observability.
Partner with BI to maintain a single source of truth for KPIs and metrics across the organization.
Lead the design and governance of the semantic data model to support Tableau Next AI features, including Tableau Pulse and Einstein Copilot, ensuring metric definitions are trusted, consistent, and AI-ready.
Define, certify, and deprecate official metrics organization-wide.
Guide governance and quality standards for AI-generated content to ensure outputs align with the organization’s trusted data standards.
Architect and Design Tableau Data Models
Develop optimized semantic layers and certified data sources for Tableau dashboards and analytics.
Implement best practices for star schema design, LOD calculations, and data blending.
Design and manage Virtual Connections and published data sources to centralize data access and enforce governance at the connection layer.
Performance Optimization
Diagnose and tune underperforming dashboards using Tableau Performance Recorder, database query analysis, and Admin Insights dashboards for site-wide performance monitoring.
Work closely with engineering to optimize SQL, indexing, and extract strategies.
Integration, Automation and Pipeline Monitoring
Collaborate with other departments to integrate Tableau Cloud with upstream systems (e.g., Salesforce, Redshift).
Partner closely with Data Engineering to monitor data pipeline health, implement validation checks across databases and Tableau data sources, and proactively identify syncing issues or failures before they impact downstream reporting.
Drive transparency across data source connections by communicating pipeline issues, failures, and potential downstream effects to impacted stakeholders in a timely manner.
Automate extract refreshes, data source updates, and quality monitoring.
Utilize the Tableau REST API and Metadata API for governance automation, bulk permission management, content migration, lineage auditing, and user provisioning.
Utilize the VizQL Data Service to expose governed published data sources to downstream applications and automated workflows.
Leverage the Platform Data API for activity monitoring, audit log ingestion, and governance reporting.
Leadership & Enablement
Guide BI developers and analysts on Tableau best practices and reusable data design.
Partner with business stakeholders to translate KPIs and reporting needs into technical solutions.
Help define and evolve the company’s enterprise BI strategy.
Qualifications
4+ years of experience in business intelligence, data architecture, or analytics engineering, with at least 3 years focused on Tableau.
Expert-level proficiency in Tableau Cloud, including site administration, performance tuning, governance, and LOD expressions.
Deep experience with Tableau data governance: Tableau Catalog, certified data sources, Virtual Connections, row-level and object-level security.
Proficiency with the Tableau REST API for governance automation workflows and the Tableau Metadata API (GraphQL) for lineage and catalog querying.
Advanced SQL skills (preferably Amazon Redshift).
Strong understanding of data modeling, star/snowflake schema, and semantic layer design.
Experience integrating Tableau with large-scale data ecosystems (ETL pipelines, APIs, or cloud data storage).
Knowledge of data governance, metadata management, and security principles.
Familiarity with the Platform Data API for activity monitoring and audit log ingestion.
Proven ability to collaborate with both technical and non-technical stakeholders.
Excellent communication skills, with a proactive approach to sharing updates on progress, timelines, and roadblocks along with proposed solutions.