Wireless Sensor Networks (WSNs) play a crucial role in various domains, such as environmental monitoring, health, and military applications. These applications necessitate the establishment of secure and efficient communication. This network encounters a major issue since routing attacks along with data tampering are highly prevalent in such networks due to their decentralized architecture and limited resources for computation that make the networks susceptible to a wide range of security threats. The existing techniques-WSN-Block, CEMT, TSRP, ORASWSN, POA-DL, AI-WSN, and EOSR are extensively used for routing but experience inefficiencies in optimizing paths that increases energy consumption drastically and also allows packet loss. In addition, the existing blockchain models for WSN security are not scalable; have high overheads of computation. To address these limitations, we propose the Secure Blockchain-Based Routing with Narwhal Optimization for WSNs (OpNa-SGCDN). Our approach employs Optimized Narwhal-Based Metaheuristic for guaranteed shortest-path communication and minimum energy consumption in optimum routing. Moreover, we provide Scalable Permissionless Blockchain Consensus Model (SP-BlockCM) features enhanced to yield a decentralized solution that is tamper-proof but with improved scalability. The attack detection function is designed by making use of a Stacked Bi-Tier Convolutional Deep Network (SBT-CDN), which is optimized by the Snow Geese Evolutionary Algorithm (SGEA). Experimental results demonstrate that our method improves energy efficiency with 94.7% as well as achieves higher detection accuracy for 96.3% and packet loss for 95.5%, both security and performance, and thus it is better than the available methods. The framework given here is thus obviously comprehensive as well as scalable for secure, energy-efficient WSN communication.