Tableau Senior Technical Lead

Job description: Job Summary Years of Exp - 10+ Primary Skills - Tableau Architect with Snowflake. Lead the architecture, design, implementation, and ongoing evolution of enterprise Data, Analytics, AI, and Cloud solutions — providing end-to-end ownership from strategy and roadmap through delivery, operations, and continuous optimization. Collaborate with cross-functional teams to execute the enterprise data and AI vision, building scalable cloud-native platforms that enable analytics, machine learning, Generative AI, Agentic AI, and intelligent business applications across research, manufacturing, quality, and corporate functions. Design and implement modern data architectures including data platforms, data warehouses, data lakes, semantic layers, APIs, data products, and self-service capabilities to support transactional, analytical, and AI-driven workloads. Architect and optimize the enterprise Snowflake platform, including data modeling, Snowpark development, Snowflake Cortex AI integration, Snowpipe automation, data sharing, Marketplace utilization, and cost/credit governance. Design, develop, and govern enterprise Tableau analytics solutions including dashboards, data stories, Tableau Server/Cloud administration, Tableau Prep data flows, and self-service analytics enablement for business users. Ensure data governance, security, privacy, metadata management, lineage, and data quality frameworks — maintaining trusted, compliant, and accessible data across Lakehouse environments. Partner with business and technology leaders to identify strategic opportunities where Data, AI, and automation can improve decision-making, operational efficiency, and business outcomes. Create and maintain the enterprise data architecture blueprint, including data models, integration patterns, reference architectures, master data strategies, and technology standards. Lead the design and implementation of secure, scalable, and resilient data pipelines using orchestration tools (e.g., Apache Airflow, Prefect, Dagster) and transformation frameworks (e.g., dbt), supporting both structured and unstructured data. Collaborate with cybersecurity, infrastructure, compliance, and application teams to ensure enterprise-grade security, governance, and operational excellence. Drive operational efficiency across cloud environments, establishing architectural standards, usage controls, and right-sizing strategies to maximize business value while minimizing spend. Ensure compliance with GxP data integrity requirements, 21 CFR Part 11, and other regulatory standards applicable to life sciences data systems. Key Responsibilities Lead the architecture, design, implementation, and ongoing evolution of enterprise Data, Analytics, AI, and Cloud solutions — providing end-to-end ownership from strategy and roadmap through delivery, operations, and continuous optimization. Collaborate with cross-functional teams to execute the enterprise data and AI vision, building scalable cloud-native platforms that enable analytics, machine learning, Generative AI, Agentic AI, and intelligent business applications across research, manufacturing, quality, and corporate functions. Design and implement modern data architectures including data platforms, data warehouses, data lakes, semantic layers, APIs, data products, and self-service capabilities to support transactional, analytical, and AI-driven workloads. Architect and optimize the enterprise Snowflake platform, including data modeling, Snowpark development, Snowflake Cortex AI integration, Snowpipe automation, data sharing, Marketplace utilization, and cost/credit governance. Design, develop, and govern enterprise Tableau analytics solutions including dashboards, data stories, Tableau Server/Cloud administration, Tableau Prep data flows, and self-service analytics enablement for business users. Ensure data governance, security, privacy, metadata management, lineage, and data quality frameworks — maintaining trusted, compliant, and accessible data across Lakehouse environments. Partner with business and technology leaders to identify strategic opportunities where Data, AI, and automation can improve decision-making, operational efficiency, and business outcomes. Create and maintain the enterprise data architecture blueprint, including data models, integration patterns, reference architectures, master data strategies, and technology standards. Lead the design and implementation of secure, scalable, and resilient data pipelines using orchestration tools (e.g., Apache Airflow, Prefect, Dagster) and transformation frameworks (e.g., dbt), supporting both structured and unstructured data. Collaborate with cybersecurity, infrastructure, compliance, and application teams to ensure enterprise-grade security, governance, and operational excellence. Drive operational efficiency across cloud environments, establishing architectural standards, usage controls, and right-sizing strategies to maximize business value while minimizing spend. Ensure compliance with GxP data integrity requirements, 21 CFR Part 11, and other regulatory standards applicable to life sciences data systems. Skill Requirements Years of Exp - 10+ Primary Skills - Tableau Architect with Snowflake. Other Requirements 1.Tableau Desktop Certified Professional is preferred.

Lead the architecture and implementation of enterprise data, analytics, and AI solutions, providing end-to-end ownership from strategy to delivery. Design and optimize Snowflake and Tableau platforms to enable scalable cloud-native analytics and intelligent business applications.

Requires over 10 years of experience as a Tableau Architect with Snowflake expertise. A Tableau Desktop Certified Professional certification is preferred, along with knowledge of GxP and regulatory standards for life sciences.

• TableauSouhaitée

Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.

• Tableau
• Snowflake
• Data Architecture
• Cloud Solutions
• Generative AI
• Agentic AI
• Snowpark
• Snowflake Cortex AI
• Tableau Server
• Tableau Prep
• Data Governance
• Apache Airflow
• dbt
• GxP
• 21 CFR Part 11
• Data Modeling

• Data & Analytics
• Technology
• Software
• Management & Leadership
• Science & Research

Formation minimale

Diplôme professionnel

Expérience minimale

10+ ans

Postuler avant le

3 sept. 2026

Langue de l’offre

anglais

Heures de travail

40 heures par semaine

Niveau d’expérience

Not Applicable