Dark energy is a leading theory to explain cosmic acceleration, and forthcoming astronomical surveys have been specifically designed to probe this mysterious energy component of our universe. This thesis addresses aspects of using large galaxy surveys to study dark energy, which requires an unprecedented understanding and mitigation of systematics -- a challenge that can be addressed on two fronts: quantification of the impacts of systematics, and new tools to mitigate them. Here, we specifically study the impacts of three key systematics: those induced by 1) the telescope observing strategy, 2) the Milky Way dust, and 3) uncertain photometric redshifts. Focusing on the Legacy Survey of Space and Time (LSST) carried out by the Vera C. Rubin Observatory, we quantify the impacts of LSST observing strategy on large-scale structure studies, which is a probe of dark energy. We demonstrate the effectiveness of large translational dithers -- telescope-pointing offsets -- in increasing LSST survey uniformity and reducing systematic uncertainties (Awan et al., 2016; LSST Science Collaboration et al., 2017) -- a result that has now been adopted for the baseline LSST observing strategy. We also study the impacts of Milky Way dust on dark energy science and demonstrate that ~25% of the default LSST survey area would not be useful for extragalactic static science given the Milky Way dust extinction, motivating the reconfiguration of the LSST survey footprint to avoid high-extinction regions of the sky (Lochner et al., 2018; Olsen et al., 2018). And finally, we present a new formalism that provides a novel way to correct for redshift contamination arising from photometric redshift estimation (Awan & Gawiser, 2020). Specifically, we first introduce a general formalism to correct for sample contamination for photometric galaxy samples when measuring two-point angular correlation functions, and then a new weighted estimator that assigns each galaxy a weight in each redshift bin based on its probability of being in that bin, thereby fully utilizing the probabilistic distance information available for photometric galaxies. While these techniques are motivated by preparations for LSST, they are applicable to other large galaxy surveys like Dark Energy Survey (DES), Dark Energy Spectroscopic Instrument (DESI), Hobby-Eberly Telescope Dark Energy Experiment (HETDEX), Euclid, and Wide-Field Infrared Survey Telescope (WFIRST).