SYNtzulu is an SNN processing element designed for low-cost and low-power FPGA devices targeting near-sensor data analysis. The system is equipped with a RISC-V subsystem responsible for controlling input/output operations, setting runtime parameters, and acting as a dynamic power manager, thus increasing its flexibility and enhancing its power efficiency. We evaluated the system, implemented on a Lattice iCE40UP5K FPGA, across a range of biosignal processing tasks employing SNNs, achieving accuracy comparable to state-of-the-art methods. Moreover, we also demonstrated the benefits of incorporating spike attention mechanisms and online refinement. SYNtzulu dissipates a maximum power of 9.5 mW during SNN inference, and 0.25 mW when idle, with a power efficiency of 50 pJ per synapse.