Top 18 Data Warehouse Engineer Interview Questions from Meituan and ByteDance
This article compiles 18 essential interview topics for data warehouse engineer roles, covering self‑introduction, architecture layering, dimensional modeling, HDFS operations, Spark vs MapReduce, join implementation, SQL challenges, OLAP selection, real‑time quality assurance, and job transition considerations.
Self‑introduction (you control the stage).
Data warehouse architecture and layering, and the benefits of this layering.
Dimensional modeling concepts, differences and trade‑offs of PK dimension modeling.
Typical subject areas in a data warehouse and how to partition them.
Describe the company's business and the most complex business scenario.
Data warehouse standards you have established and details of each.
Specific actions taken in model‑optimization projects and the resulting gains.
Read/write process of HDFS (client, NameNode, DataNode).
Scenarios of data skew and mitigation methods.
Comparison between Spark and MapReduce, including number of map and reduce tasks.
Differences between wide and narrow dependencies in Spark.
Implementation principles of join operations.
SQL interview questions: (1) user retention model, (2) peak‑valley SQL, (3) consecutive n‑day login.
Topic modeling vs process modeling: applicable scenarios and how to implement.
OLAP database technology selection and why ClickHouse is chosen.
Major challenges of offline data warehouses, how to overcome them, and whether a methodology has been codified.
How real‑time data warehouses ensure data quality, including tools and techniques.
Reasons for changing jobs and the shortest possible onboarding time.
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