Primary Skills - Tableau Architect with Snowflake.

Location - Nearshore to Cover 1:00 PM to 6:00 PM EST

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.