For data teams focused on A/B testing, Python offers a range of powerful libraries and data engineering tools that facilitate the design, implementation, and analysis of experiments. These libraries are essential for running statistical tests, visualizing results, and automating the testing process, allowing data teams to make informed decisions based on robust data analysis.