Tanmay's response aligns well with the benchmark response, demonstrating comfort with Python and SQL for data engineering tasks. He mentions using Python libraries like Pandas and NumPy for data manipulation, and Matplotlib and Seaborn for visualization, which matches the benchmark. He also highlights writing reusable scripts and SQL query optimization, reflecting applied experience in data engineering tasks. However, he could enhance his response by providing specific examples of projects or tasks where these skills were applied, which would strengthen his demonstration of applied experience.