Consider a scenario where you are processing time series data from weather stations using Spark Structured Streaming. The data includes temperature and humidity readings from various stations. How would you structure your Spark job to process this data efficiently, including handling data across partitions and within one partition? Additionally, describe how you would manage any potential schema changes in the incoming data.