Meesho PySpark Interview Questions for Data Engineers in 2025 Preparing for a PySpark interview? Let’s tackle some commonly asked questions, along with practical answers and insights to ace your next Data Engineering interview at Meesho or any top-tier tech company. 1. Explain how caching and persistence work in PySpark. When would you use cache() versus persist() and what are their performance implications? Answer : Caching : Stores data in memory (default) for faster retrieval. Use cache() when you need to reuse a DataFrame or RDD multiple times in a session without specifying storage levels. Example: python df.cache() df.count() # Triggers caching Persistence : Allows you to specify storage levels (e.g., memory, disk, or a combination). Use persist() when memory is limited, and you want a fallback to disk storage. Example: python from pyspark import StorageLevel df.persist(StorageLevel.MEMORY_AND_DISK) df.count() # Triggers persistence Performance Implications : cache() is ...
My Power BI Journey: Answering #ScatterPie Analytics 1st Round Today, I’m sharing my responses to a series of Power BI questions which has been asked in the #ScatterPie Analytics 1st Round interview. These questions not only tested my technical expertise but also explored how I approach problem-solving in real-world scenarios. Here's how I responded: 1. Walk Me Through Your Profile I am a Sr. Data Analyst with over 3.5 years of experience specializing in data visualization and reporting. I have developed dynamic dashboards and reports in Power BI, leveraging my expertise in DAX, SQL, and data modeling . My work spans domains like sales, marketing, operations, and finance, delivering actionable insights that drive business decisions. I’ve also managed Row Level Security (RLS) implementations and optimized performance for datasets with millions of rows. 2. How Many Dashboards Have You Developed So Far? I have developed 20+ dashboards , catering to diverse business needs. For instan...