Data Engineer & Data Architect Interview Prep MasterclassPublished 5/2026
Created by Deepak Dubey
MP4 |
Video: h264, 1920x1080 |
Audio: AAC, 44.1 KHz, 2 Ch
Level: Beginner |
Genre: eLearning |
Language: English |
Duration: 9 Lectures ( 5h 45m ) |
Size: 5.4 GB
⚡ Master 90+ real-world interview questions across Apache Spark, Kafka, and Airflow asked at top product and data-driven companies.
⚡ Confidently explain core architecture, internals, and performance tuning concepts for Spark, Kafka, and Airflow in technical interviews.
⚡ Tackle scenario-based and system design questions on building scalable data pipelines, streaming systems, and workflow orchestration.
⚡ Prepare for Data Engineer and Data Architect roles with structured, interviewer-approved answers you can adapt to your own experience.
Requirements❗ Suitable for aspiring or working Data Engineers, Analysts, and Software Engineers preparing for Data Engineer or Data Architect interviews. Basic SQL and Python knowledge recommended.
DescriptionAre you preparing for a Data Engineer or Data Architect interview and feeling overwhelmed by the sheer number of tools, concepts, and edge cases you're expected to know?Apache Spark, Apache Kafka, and Apache Airflow are the three pillars of nearly every modern data engineering interview - yet most candidates walk in with surface-level answers and walk out wishing they had prepared differently.
This course is built to fix exactly that.
Inside, you'll find
90+ carefully curated interview questions - 30 each on Spark, Kafka, and Airflow - paired with structured, scenario-based answers. Each question is broken down with the concept behind it, a clear way to frame your response, and the trade-offs an experienced interviewer might dig into.
What you'll get inside✨
30 Apache Spark questions covering RDDs, DataFrames, Catalyst optimizer, Tungsten, partitioning, shuffles, caching, broadcast joins, skew handling, and performance tuning
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30 Apache Kafka questions spanning topics, partitions, consumer groups, offsets, replication, exactly-once semantics, Kafka Connect, Kafka Streams, and real production failure scenarios
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30 Apache Airflow questions on DAGs, operators, executors, scheduling internals, XComs, sensors, dynamic DAGs, retries, SLAs, and orchestrating real-world pipelines
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Scenario-based framing so you learn how to answer "how would you design / debug / optimize." questions - not just definitions
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Patterns and trade-offs you can adapt to your own projects and experience, making your answers sound senior, not scripted
Who this course is for⭐ Anyone targeting Data Engineer or Data Architect interviews who wants structured, scenario-based answers covering the modern data stack.
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