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Pandas
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
pandas: you mention employability, and this is one of the most powerful ways you can wrangle with data in Python, say as a data analyst. I have used it for some of my research projects because it allows you to collect elements from a data table easily based on shared characteristics or a custom function and plot/perform statistical analysis on them.
NumPy: allows you to work with matrices and common math functions efficiently. Very useful for analyzing experimental data and running simulations.