Big Data Interview Experience Summary: Topics, Weightings, and Key Takeaways
The article shares a detailed interview experience for big‑data roles, outlining the proportion of problem‑solving, project, fundamentals, and open‑question segments, and highlights the technical depth expected in areas such as Flink, Hudi, SparkSQL, and OLAP.
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1. Problem‑Solving (10%)
Prepared Hot100 easy, medium, and common hard questions plus SQL problems; two companies asked algorithm questions, emphasizing clear communication of thought process.
Algorithm questions typically appear at the final interview stage and are relatively relaxed if earlier performance was strong.
2. Project Interview (60%)
All interviewers probed past projects, focusing on business background, technical solutions, and detailed implementation.
Interviewers delved deeply into difficult points, sometimes requesting pseudo‑code.
Scenario‑based design questions required candidates to propose architecture, core implementation, and potential issues, testing comprehensive ability and vision.
Senior interviewers (often TLs) asked extensive solution‑oriented and design questions.
3. Fundamentals and Production Practice (20%)
First‑ and second‑round interviewers asked core framework principles related to the candidate’s resume.
Key topics included Flink, Hudi, SparkSQL, and OLAP, matching the candidate’s primary tech stack.
All rounds covered production‑environment questions such as operational challenges, current practices, and future upgrades.
4. Open‑Ended Questions (10%)
These appeared in later technical rounds and covered industry trends, future direction of specific tech stacks, as well as non‑technical aspects like communication, project value assessment, and team management.
Overall Impression
The current interview landscape emphasizes practical experience and solid fundamentals; the “八股文” (core knowledge) cannot be neglected, making interviews noticeably tougher than 2–3 years ago.
One company’s second‑round interview lasted two hours, after which the TL added the candidate on WeChat and strongly invited them to join.
Market conditions have shifted; offers are no longer abundant, but strong personal capability still yields many opportunities.
Peers in the industry can stay optimistic, while newcomers should maintain a positive outlook, set high personal standards, and recognize that every direction is highly competitive both domestically and abroad.
Ultimately, while external circumstances may not change, personal growth and adaptation are essential.
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Big Data Technology & Architecture
Wang Zhiwu, a big data expert, dedicated to sharing big data technology.
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