Sr. Data Platform Architect

Nutanix•San Jose, CA

1d•Hybrid

About The Position

Are you a visionary data architect with a passion for turning innovative designs into scalable, production-ready solutions? If so, you will thrive in our dynamic team at Nutanix, where you will have the opportunity to shape cutting-edge data platform architecture, drive enterprise-level data strategies, and collaborate with talented professionals to enable impactful analytics and machine learning initiatives. We are seeking a hands-on, driven, and innovative Senior / Staff Data Platform Architect to define, build, and scale the enterprise data platform foundation. This role requires an architect who can move from strategy to working solutions — shaping the roadmap, setting engineering standards, and driving complex designs into production. The role leads core platform architecture across ingestion, storage, compute, orchestration, security, governance integration, observability, and operations. The successful candidate will build a resilient, secure, AI-ready platform that enables Data Engineering, BI, Analytics, and ML/AI teams to deliver trusted data products at enterprise scale. This role owns technical data platform architecture, engineering frameworks, and production-grade solution delivery. It does not own enterprise semantic-layer design, KPI harmonization, business metric definitions, dashboard interpretation standards, or business terminology governance; those responsibilities remain with the analytics / semantic-layer architecture function.

Requirements

12+ years of experience in data architecture, engineering, or related fields; 5+ years in large-scale data platforms.
Proficient in designing and implementing solutions using SQL, Apache Spark, ETL/ELT frameworks, and orchestration tools.
Strong understanding of data storage formats, lifecycle management, and performance optimization techniques.
Hands-on experience with cloud technologies and platforms like Kubernetes, Trino, Dremio, and Informatica.
Expertise in implementing security controls such as RBAC, encryption, and audit logging for data governance.
Ability to drive architectural decisions and collaborate with cross-functional teams effectively.
Experience with DevOps practices, CI/CD, and infrastructure-as-code for seamless data platform operations.
Bachelor's degree in Computer Science, Engineering, or related technical field; advanced degree preferred.

Responsibilities

Lead the design and implementation of a scalable, resilient enterprise data platform integrating advanced technologies and best practices.
Establish and enforce architecture standards for data ingestion, storage, processing, and security to drive efficient operations and data quality.
Collaborate cross-functionally with Data Engineering, BI, Analytics, and ML/AI teams to create streamlined access to trusted data.
Construct reusable engineering frameworks for efficient ETL/ELT processes, automation, and data lifecycle management.
Drive observability and performance optimization strategies, ensuring the platform meets defined reliability and performance objectives.
Mentor engineering teams on scalable design principles, production-readiness, and operational excellence to foster a culture of innovation.
Evaluate and assess emerging technologies, leading proof-of-concepts to identify opportunities for platform enhancements and future scalability.
Set clear first-year objectives, including successful deployment of key platform features, improved data quality metrics, and enhanced operational monitoring systems.