Organizations are collecting massive amounts of data, projected to reach 180 zettabytes by 2025. To support modern business operations, analytics, and AI-driven insights, a scalable and resilient data platform architecture is crucial. Key principles for architecting such a platform include understanding core concepts like scalability and resilience, incorporating appropriate components for storage, ingestion, processing, and security, and designing for scalability and resilience through strategies like horizontal scaling, redundancy, failover systems, backups, disaster recovery, monitoring, chaos engineering, and load balancing. Adopting best practices such as microservices architecture, autoscaling, continuous monitoring, caching, and automation can help ensure long-term success in building a robust data platform capable of handling future growth and maintaining system performance and uptime.