Senior Data Architect, Semantic Layer & Gen AI Readiness

Nutanix•San Jose, CA

6d•Hybrid

About The Position

Are you a forward-thinking data architect with a passion for driving innovation in analytics, a proven track record in semantic modeling, and an ability to align cross-functional stakeholders around a common vision? If so, you’ll thrive in a dynamic environment at Nutanix, where your expertise will be the cornerstone of our transition to AI-enabled decision-making and trusted analytics, empowering teams to deliver insights that drive meaningful business outcomes. At Nutanix, the Data Analytics team is a dynamic group of over 50 collaborative and innovative professionals spread across the US and India. This diverse team consists of data scientists, analysts, and engineers who work together to drive insights and enhance decision-making through data-driven strategies. The culture within the team fosters open communication, encourages fresh ideas, and values each member's contribution, making it an exciting environment for those passionate about analytics and technology. You will report to the Sr. Director of Data Analytics, who prioritizes mentorship and professional development while leading a supportive team environment. This position is a hybrid role, requiring you to work in the office for three days a week at our headquarters in San Jose, CA, providing the opportunity to collaborate in person with your colleagues while also allowing for flexibility. Travel requirements for this role are minimal, ensuring you can focus on your work without frequent disruptions.

Requirements

Bachelor’s degree in Computer Science, Information Systems, Engineering, Business Analytics, or a related field; Master’s degree preferred.
10+ years of experience in analytics architecture, business intelligence, or enterprise analytics transformation.
Proven expertise in designing and implementing scalable semantic models and governed analytical layers.
Strong ability to translate complex business concepts into usable analytical structures with effective metrics standardization.
Experience in cross-domain collaboration to define shared metrics and resolve KPI inconsistencies.
Knowledge of practical applications of AI in analytics, ensuring trust and governance.
Exceptional interpersonal, written, and verbal communication skills for engaging both technical and business stakeholders.
Proficiency in data governance, metadata management, and enhancing self-service analytics through user-friendly data models.

Responsibilities

Architect and implement a robust enterprise semantic layer that standardizes business logic across all domains.
Collaborate with key stakeholders to define and harmonize essential business metrics, dimensions, and interpretations.
Facilitate the transition from traditional reporting methods to innovative, AI-driven analytics solutions.
Identify and integrate AI capabilities into analytics workflows to enhance insights and streamline decision-making processes.
Establish and enforce standards for semantic modeling, governance, and lifecycle management across the organization.
Drive stakeholder engagement initiatives to promote adoption of semantic standards and ensure consistent usage of analytic tools.
Resolve inconsistencies in KPIs and improve the reliability of dashboards and analytics outputs.
Achieve a unified understanding of business terminology and metrics, fostering organizational alignment and trust in analytics.