1 general DSA + 1 domain-specific (Python or SQL)
Out loud, in order: clarify, build it, check it, explain it.
Practise SQLLoadingone moment…
Data engineering interview · Big Tech & Enterprise Software
SQL-weighted DE loop that probes real production data work: backfilling billion-row tables and evolving schemas without downtime.
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And what its data engineers work with.
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Stages in the order candidates meet them.
6 stages. 3 rounds have reported questions, described below.
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The topics it covers and the questions candidates reported.
1 reported question. See them below
2 reported questions. See them below
distinctive
Medium confidence3 reported questions. See them below
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By round. Questions marked Expected are written from the company's standards.
CodingMedium confidence
SQLMedium confidence
Production data / pipelineMedium confidence
Nobody reported these exact questions at NVIDIA. They are the questions a loop for each of its top topics is known to ask, so prepare for them as likely, not as confirmed.
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Ranked by how much of the evidence points at each topic.
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Do the first group before the second.
SQL (window, optimization)
Do first (3)Production data ops (backfill, schema evolution without downtime, CI/CD, fault tolerance)
Clean testable Python; scalable ETL/data-lake design
Spark/Databricks
ThenDSA
Behavioral
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Why candidates were turned down, as reported.
No real production data experience (backfill, schema evolution, data quality)
Modeling is named in 14 of 50 company accounts.Weak SQL optimization
SQL is named in 37 of 50 company accounts.Non-testable code
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2 reported, 3 composite. Each opens and closes. Composites are labelled.
In Taipei in 2025 the first round had three interviewers asking about coding, leadership, behavior and experience. The second round was SQL and experience. The last round was system design, with a question about predicting GPU server failures in real time. The whole process took about three months.
What to take from it Expect a long process and a design round on real-time data.
Another Taipei candidate had a technical round and a take-home task, and also said the process took about three months.
What to take from it Plan for a take-home and a slow timeline.
Composite walkthroughs. Built from the company's documented loop, not from one person's account.
This is a composite, not one person's account. It follows a staff-level loop: a recruiter call, coding, SQL-heavy data engineering, a production round (backfilling a billion-row table, changing a schema without downtime, CI/CD), system design and behavioral.
What to take from it Use it to see how production questions can appear.
This is a composite, not one person's account. It is built from the loop we have on record for NVIDIA. Questions reported for this round: 1 general DSA + 1 domain-specific (Python or SQL).
What to take from it Practise these questions before you reach this round.
This is a composite, not one person's account. It is built from the loop we have on record for NVIDIA. Questions reported for this round: Window functions; Optimization strategies.
What to take from it Practise these questions before you reach this round.
DE-specific first-hand reports were sparse; the production-data probes (backfill, schema evolution) are the distinctive signal.
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Their reported questions, one at a time, against a stopwatch.
1 general DSA + 1 domain-specific (Python or SQL)
Out loud, in order: clarify, build it, check it, explain it.
Practise SQL10
Pick your level and the weeks you have.
Built from what NVIDIA asks, strongest first. For the wider basics at your level, follow the Mid level plan alongside it.
Python and coding
Read: Python chaptersDrill: Python practiceSay it aloud: Python questionsFull plan: Ace the Python round
Data modeling
Read: Data modeling chaptersDrill: Modeling practiceSay it aloud: Data modeling questionsFull plan: Ace the modeling round
Pipeline and system design
Read: Data pipeline chaptersDrill: Pipeline practiceSay it aloud: Data pipeline questionsFull plan: Ace the pipeline round
Behavioral and communication
Read: Behavioral storytellingSay it aloud: Behavioral questions
Cloud and tools
Rehearse the NVIDIA loop
Run the question deckThen repeat your weakest topic once more.