The Monash Time Series Forecasting Repository contains multiple different time series datasets from various domains. These have been collected from forecasting competitions or other previous forecasting use, so you should also be able to learn something from previous work that used a particular dataset.
Some of the datasets included should show clear seasonality, even if they are not sales. Specifically, I am thinking of the Tourism and the Electricity datasets. These may even exhibit multiple seasonalities - for instance, the Electricity dataset contains hourly data, and of course there are seasonalities within each day, but the intra-daily seasonality differs between weekdays and weekends. (For that matter, so does StackExchange traffic, which you can also download.)
An introduction and description of the repository, along with more information about the datasets, is given by Godahewa et al. (2021).
Alternatively, take a look at the M5 forecasting competition, which I believe is not (yet) contained in the Monash Repository. It's daily sales on a store $\times$ SKU level from multiple Walmart stores. The weekly seasonality may not be visible on the lowest level of aggregation, but it should become clear once you aggregate SKUs up to categories.