Groundwater plays a vital role in Ethiopia's water security, yet its long-term dynamics and drought behaviour remain poorly understood due to sparse monitoring and reliance on precipitation-based indicators. This study investigates groundwater (GW) storage dynamics and groundwater drought characteristics across Ethiopia during 2003-2024, using combined data from the Gravity Recovery and Climate Experiment and its follow-on mission, together with outputs from the Global Land Data Assimilation System land-surface model. Groundwater storage anomalies (GWSA) were derived, and groundwater drought was quantified using a Standardized Groundwater Drought Index (SGDI). Multi-timescale relationships between meteorological drought (SPI at 1-24 months) and groundwater drought were studied across 12 major river basins and aridity-based climate zones, while the influence of large-scale climate teleconnections (Ni & ntilde;o3.4, DMI, and EMI) was assessed using cross-wavelet coherence analysis. Results reveal pronounced spatial heterogeneity in groundwater storage behaviour, with stronger SPI-SGDI coupling during longer accumulation periods (12-24 months), with peak correlations exceeding 0.6 in several basins, indicating substantial groundwater memory and delayed drought propagation. This research underscores the importance of satellite data in monitoring groundwater drought in Ethiopia, where in situ data are limited. Groundwater drought conditions (SGDI < - 1) occurred during approximately 10-15% of the study period at the national scale, with mean event durations of 3-4 months and maximum durations exceeding 6 months in arid and semi-arid regions. Teleconnection impacts were intermittent and scale-dependent, with Ni & ntilde;o3.4 and DMI accounting for 15-25% of groundwater drought variability during specific periods, while local hydroclimatic factors exerted dominant control. These findings highlight the cumulative nature of groundwater drought in Ethiopia and demonstrate the value of satellite gravimetry for groundwater drought monitoring and water-resources management in data-scarce regions.