Tiger Analytics | Data Engineer Interview Questions Spark Optimization, DLT & More | Part 2

Most candidates walk into a Tiger Analytics Data Engineer interview underprepared. This video covers the 6 topics that actually come up — with real answers and a breakdown of what the interviewer is really looking for. 🔥 Topics Covered: ✅ Delta Live Tables (DLT) — Batch vs Streaming ✅ Data Quality and Data Integrity ✅ End-to-End Project Architecture ✅ Schema Evolution Strategies ✅ Spark Optimization Techniques ✅ Data Partitioning and Performance Benefits 👨‍💻 Role Level: Mid-Level Data Engineer (3–6 years) 🏢 Company: Tiger Analytics 📌 If you're preparing for a Data Engineer interview at Tiger Analytics or any Databricks-heavy company, this video is for you. 🔔 Subscribe to Crack Data Engineering for more company-specific interview prep — in Hinglish! #DataEngineering #TigerAnalytics #SparkOptimization #DeltaLiveTables #DataEngineerInterview #Databricks #CrackDataEngineering #InterviewPrep #Hinglish