Google Data Engineer candidates report recruiter screens, SQL and Python coding, pipeline and data-modeling design, and behavioral or team-matching conversations. Reports are mixed, so prepare broadly.
$175K
Avg. Base Comp
$307K
Avg. Total Comp
Not reported
Typical Rounds
Not reported
Process Length
Candidates describe the Google Data Engineer interview as a mix of practical data work and general engineering. The most repeated theme is SQL beyond the basics. One candidate who did not advance was pushed on edge cases after getting a working query. Another reports non-trivial SQL plus analytical schema design, including normalization tradeoffs, partitioning and clustering.
Pipeline design also shows up often. Two candidates describe ETL or streaming prompts: a real-time clickstream or ad-click pipeline, and ETL handling of late-arriving data, duplicates and errors. The candidate with the clickstream prompt reported an offer. Be ready to explain batch versus streaming, idempotency and failure cases out loud. One senior candidate in an early role-knowledge round was asked open-ended operational questions: triaging 100 daily alerts, rising BigQuery cost, and automated reports for 1,000 merchants.
Coding is not absent. Reports mention tree and graph traversal, a binary-search follow-up, parsing CSV-style data, and an islands-style tree question. One candidate rated the problems easy to medium but still felt real time pressure. Practice explaining complexity while you code.
Structure varies a lot. One candidate describes a five-round onsite covering modeling, pipeline design, Python, SQL and Googleyness. Others report only a recruiter call plus one SQL round, a process with an online test, group discussion and HR round, or team-matching conversations after the technical stage. Ask your recruiter what your loop includes, and prepare to discuss your resume in concrete terms.
Synthesized from 13 candidate reports by our editorial team.
Had an interview recently?
Share your experience. Unlock the full guide.
Real interview reports from people who went through the Google process.
Share your own interview experience to unlock all reports, or subscribe for full access.
Sourced from candidate reports and verified by our team.
Topics based on recent interview experiences.
Featured question at Google
Write a query that returns all neighborhoods that have 0 users.
| Question | |
|---|---|
| 2nd Highest Salary | |
| Top Three Salaries | |
| Merge Sorted Lists | |
| Experiment Validity | |
| String Shift | |
| Last Transaction | |
| Top 3 Users | |
| Third Purchase | |
| First Touch Attribution | |
| Minimum Change | |
| Find the First Non-Repeating Character in a String | |
| Daily Retention Summary | |
| RMS Error | |
| Find Bigrams | |
| Detecting ECG Tachycardia Runs | |
| Size of Joins | |
| The Brackets Problem | |
| Good Grades and Favorite Colors | |
| Level Of Rain Water In 2D Terrain | |
| Google Maps Improvement | |
| Cyclic Detection | |
| Sort Strings | |
| WAU vs Open Rates | |
| Radix Addition | |
| Most Repetition | |
| Bucket Test Scores | |
| Complete Addresses | |
| Find the Index with Equal Left and Right Sum | |
| Hurdles In Data Projects |
Synthesized from candidate reports. Individual experiences may vary.
Candidates report an initial recruiter conversation about their background, communication and prior work. One candidate was contacted directly by a recruiter and mentions that another applicant completed a soft-skills assessment before recruiter contact. Confirm with your recruiter which steps apply to you.
Candidates report a first technical round that may combine advanced SQL with Python data manipulation, sometimes on CoderPad. Others describe a SQL coding round that probed edge cases, or open-ended questions on alerts, BigQuery cost and reporting systems. The format appears to vary by candidate, so prepare for SQL first.
Some candidates describe LeetCode-style coding. Reports mention tree and graph traversal, a binary-search follow-up, CSV-style data parsing, and an islands-style tree question, with one candidate describing easy-to-medium problems under time pressure. Interviewers wanted a clear explanation of approach and complexity along with working code, so practice narrating your reasoning while you solve.
Candidates report design discussions on real-time clickstream pipelines, ETL with late data and duplicates, star schemas, slowly changing dimensions and analytical schema tradeoffs. One candidate noted that GCP tools such as BigQuery, Dataflow and Pub/Sub may come up if they are on your resume. Expect tradeoff discussion rather than tool naming alone.
Reports describe a Googleyness and behavioral conversation in one onsite loop, a group discussion and HR round in another process, and case-study-style questions in a third. One candidate went through two team-matching rounds after the technical stage before matching. Those conversations focused on knowing your resume and connecting your experience to the team's work.
