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 ...
Deloitte Recent Interview Insights for a Data Analyst Position (0-3 Years) When preparing for an interview with a firm like Deloitte, particularly for a data analyst role, it's crucial to combine technical proficiency with real-world experiences. Below are my personalized insights into common interview questions. 1. Tell us about yourself and your current job responsibilities. Hi, I’m [Your Name], currently working as a Sr. Data Analyst with over 3.5 years of experience. I specialize in creating interactive dashboards, analyzing large datasets, and automating workflows. My responsibilities include developing Power BI dashboards for financial and operational reporting, analyzing trends in customer churn rates, and collaborating with cross-functional teams to implement data-driven solutions. Here’s a quick glimpse of my professional journey: Reporting financial metrics using Power BI, Excel, and SQL. Designing dashboards to track sales and marketing KPIs. Teaching data analysis conce...