Technical Architect — Tableau Next

Role Overview
The Technical Architect for Tableau Next is an execution-focused analytics architect and primary subject matter expert for the Tableau Next platform. You will design and deliver migrations from Salesforce CRM Analytics, Cognos, Business Objects, MicroStrategy, Power BI, Looker, and legacy Tableau Server to a modern data stack. As the primary technical authority for this migration track, you will own the Tableau Next analytics platform architecture, legacy content migration strategy, and feature adoption roadmap.
Operating at the forefront of the modern data stack, you will architect scalable and secure solutions that bridge Data Cloud’s foundational architecture with Tableau Next. You will combine deep Analytics, Data 360, and Salesforce knowledge to ensure dashboards, data sources, permissions, and security structures are migrated with full fidelity, improved performance, and accelerated time-to-insight for business users.
You will use approved enterprise AI tools as an authorized input to relevant architecture, migration, analysis, and documentation work. You will validate AI-assisted outputs, test assumptions, protect sensitive information, and remain accountable for technical decisions, migration quality, and customer outcomes.
Core Responsibilities
Tableau Next Platform Ownership: Act as the definitive technical authority for Tableau Next, leading the end-to-end transition of dashboards and reporting from Salesforce CRM Analytics, Cognos, Business Objects, MicroStrategy, Power BI, Looker, and legacy Tableau Server.
AI-Assisted Architecture and Migration: Use approved enterprise AI tools to support architecture documentation, legacy-to-target mappings, migration planning, test-case development, diagnostics, and technical communications. Apply expert judgment to validate outputs and preserve business logic, data fidelity, and platform compatibility.
Security and Governance Architecture: Design and implement comprehensive data governance and security frameworks within the new architecture, enforcing policy-based data visibility and row-level security (RLS) to ensure strict, role-aligned data access.
Human Accountability and Validation: Review AI-assisted recommendations, mappings, and analysis for accuracy, completeness, security, privacy, and alignment with approved architecture and governance standards before they inform delivery or customer decisions.
Data Source Architecture: Architect the data source framework using Analytics, Data 360, and Salesforce knowledge to design live connections and optimized models tailored for Tableau Next.
Data Ingestion and Engineering: Own and manage data ingestion directly within Salesforce Data Cloud to power the Tableau Next reporting layer.
Semantic Layer Design: Design and build the semantic layer strictly within Salesforce Data Cloud to support all Tableau Next analytical requirements.
Model Translation: Map and translate legacy BI semantic models into Data Cloud Calculated Insights and semantic models, using structured validation to confirm business logic equivalence.
Data Lineage: Define end-to-end data lineage, ensuring business logic equivalence is preserved when migrating fields through Data Cloud transformation layers.
Discovery and Strategy: Lead functional and technical discovery workshops with client teams to assess legacy report complexity, usage analytics, and data source dependencies.
Advisory: Serve as a Trusted Advisor to Analytics leaders and Enterprise Architects to shape the Tableau Next migration roadmap, self-service analytics vision, and data governance strategy.
Migration Standards: Establish best-in-class standards for the migration practice, building reusable Tableau Next dashboard templates, Data Cloud connection frameworks, migration validation methods, and governance playbooks.
Execution and Cutover: Plan and execute cutover strategies, including legacy BI deprecation, user access migration, and post-go-live enablement.
Risk Mitigation: Identify and proactively mitigate technical risks related to data source credentials, calculated field logic parity, RLS re-implementation, extract refresh SLAs, data readiness, and AI-assisted migration outputs.
Technical Communication: Translate architecture decisions, migration risks, data limitations, and validation findings into clear guidance for client teams, Analytics leaders, and Enterprise Architects.
Strictly Required Qualifications (Must-Haves)
Tableau Next: Comprehensive, hands-on mastery of the Tableau Next platform, including advanced dashboarding, platform capabilities, and usage reporting.
Salesforce Data Cloud Expertise: Deep technical understanding of data connections, data ingestion, Data Streams, Data Lake Objects (DLOs), Data Model Objects (DMOs), Data Governance, and Calculated Insights.
Data Governance and Security: Proven ability to design and execute complex data governance models, specifically implementing policy-based data visibility and row-level security (RLS).
Salesforce CRM Analytics: Proven experience and technical depth in CRM Analytics, formerly Einstein Analytics.
Semantic Models: Advanced ability to design, build, and migrate semantic layers, specifically within the Salesforce Data Cloud architecture.
Salesforce Administrator Knowledge: Deep understanding of Salesforce platform administration, security models, and user management.
Salesforce Core Platform: Functional knowledge of at least one Salesforce Cloud, such as Sales Cloud, Service Cloud, or Financial Services Cloud.
AI-Fluent Technical Practice: Demonstrated ability to use approved enterprise AI tools or comparable authorized AI-assisted methods for role-relevant work products such as architecture documentation, migration mappings, test cases, diagnostics, or technical analysis, with human validation and accountability for the final result.
Preferred Qualifications (Good-to-Have)
Knowledge of Salesforce Data Cloud One.
Experience migrating from IBM Cognos, SAP Business Objects, MicroStrategy, Microsoft Power BI, Looker, or legacy Tableau Server to Tableau Next.
Familiarity with Tableau Site and Governance Architecture, including project hierarchy, permission models, and content certification workflows.
Understanding of broader cloud data platform integrations, including Snowflake, Databricks, BigQuery, and Azure Synapse, as secondary analytical sources.
Knowledge of dbt, Apache Airflow, or similar orchestration tools for upstream data pipeline dependencies.
Familiarity with Tableau Embedded Analytics for migrating legacy embedded BI into external applications.
Understanding of Tableau Bridge for on-premises data source connectivity.
10+ years of general experience in Business Intelligence, analytics, and data platform solutions.
5+ years of hands-on analytics development and architecture experience.
Certification Requirements
Required Certifications
Salesforce Certified Administrator
Salesforce Certified CRM Analytics and Einstein Discovery Consultant
Highly Desired (Very Strong Plus)
Salesforce Data Cloud Consultant
Tableau Desktop Specialist
Nice to Have
Tableau Certified Architect
Tableau Certified Data Analyst
Snowflake SnowPro Core or Advanced
Databricks Certified Associate Developer
dbt Analytics Engineering Certification

Employment type
Full time