Empowered by Internet of Things (IoT) and cloud computing platforms, the concept of smart cities is making a transition from conceptual models to development and implementation phases. Multiple smart city initiatives and services such as Smart Grid and Smart Meters have emerged that have led to the accumulation of massive amounts of energy big data. Big data is typically characterized by five distinct features namely, volume, velocity, variety, veracity, and value. To gain insights and to monetize big data, data has to be collected, stored, processed, analyzed, mined, and visualized. This paper identifies the primary layers of a big data architecture with start-of-the-art communication, storage, and processing technologies that can be utilized to gain meaningful insights and intelligence from big data. In addition, this paper gives an in-depth overview for research and development who intend to explore the various techniques and technologies that can be implemented for harnessing big data value utilizing the recent big data specific processing and visualization tools. Finally, a use case model utilizing the above mentioned technologies for Smart Grid is presented to demonstrate the energy big data road map from generation to monetization. Our key findings highlight the significance of selecting the appropriate big data tools and technologies for each layer of big data architecture, detailing their advantages and disadvantages. We pinpoint the critical shortcomings of existing works, particularly the lack of a unified framework that effectively integrates these layers for smart city applications. This gap presents both a challenge and an opportunity for future research, suggesting a need for more holistic and interoperable solutions in big data management and utilization.