Coinbase Data Engineer Interview Guide

The Coinbase data engineer loop, round by round: what each stage tests, example questions with the guidance interviewers actually score, the mistakes that sink strong candidates, and how to prepare.

Last updated: Proudly published by: Jeff Wahl

What the Coinbase loop tests: domains and difficulty

Our prediction of the question mix by domain and difficulty for this company's data engineer loop, from live listings and interview reports.

By domain
SQL
57%
8
Python
43%
6
By difficulty
Easy
50%
7
Medium
29%
4
Hard
21%
3

The domain and difficulty mix we predict for a Coinbase data engineer loop, across 14 problems. It updates as more Coinbase data lands.

Updated 14 predicted Coinbase problems

3 real Coinbase interview questions

Reported by candidates from real loops, tagged by domain, round, level, and year. Expand for what the round is scoring.

SQLL4 · 2024
Given signup and activity tables, compute user retention rates by monthly cohort.
Phone screen · screen sql
+

Write a SQL query that computes month-over-month retention rates for user cohorts. Given a signups table (user_id, signup_date) and an activity table (user_id, activity_date), group users by their signup month (cohort), then for each subsequent month compute the fraction of that cohort who were active. Requires date truncation, conditional aggregation or window functions, and self-join or CTE patterns.

SQLL5 · 2024
Compute a rolling window aggregate over bank transaction data using ROWS/RANGE frame specification.
Onsite · sql
+

Given a bank transactions table (transaction_id, user_id, amount, transaction_date), compute a rolling aggregate (e.g., rolling 7-day sum of transaction amounts per user). The interviewer specifically tests knowledge of window frame clauses: ROWS BETWEEN N PRECEDING AND CURRENT ROW versus RANGE BETWEEN. Candidate must articulate the difference between ROWS and RANGE semantics.

PythonL4 · 2025
Implement a Least Recently Used (LRU) cache using OrderedDict or doubly-linked list plus hashmap.
Phone screen · screen python
+

Implement a data structure that supports get(key) and put(key, value) in O(1) time. The cache has a fixed capacity; when full, it evicts the least recently used entry. Accepted approaches: Python collections.OrderedDict with move_to_end(), or a custom doubly-linked list with a hashmap for O(1) lookup. Must explain the time complexity of each operation.

Try a Coinbase-style SQL round

Find every user active on 3 or more CONSECUTIVE days. This gaps-and-islands shape shows up in nearly every DE SQL round. Edit the query and run it against the seed data.

/* Users active on 3+ consecutive days. */
/* Hint: date minus a per-user ROW_NUMBER is constant within a streak. */
WITH streaks AS (
SELECT
user_id,
activity_date,
activity_date - CAST(
(ROW_NUMBER() OVER (
PARTITION BY user_id
ORDER BY activity_date
))
AS INT
) AS grp
FROM user_sessions
)
SELECT
user_id
FROM streaks
GROUP BY user_id, grp
HAVING COUNT(*) >= 3

Practice the Coinbase loop

The problems our model expects in this company's interview, grouped by round. Work the shapes that come up, not the ones that read well on a list.

Coinbase is hiring data engineers now

The roles behind this loop. Prep against the levels and locations they are actually filling.

Coinbase compensation and culture

The numbers, tech stack, and team structure live on the company overview.

Coinbase data engineer roles by level

Level-specific pages: the comp, the bar, and what the loop tests at each seniority.

Compare Coinbase with other data engineering employers

How the role, pay, and loop stack up against peer companies.

02 / Why practice

Prepare at Coinbase interview difficulty

  1. 01

    Reading a solution is not the same as writing one

    Every engineer who has frozen on a query they had read a dozen times knows the gap. The only preparation that closes it is producing the answer yourself, under time, before the interview does it for you

  2. 02

    76% of hiring managers reject on the coding task, not the resume

    From HackerRank's 2024 Developer Skills Report. Candidates who look strong on paper still fail the live screen if they haven't done timed, executable practice

  3. 03

    5 problem shapes cover 80% of data engineer loops

    Dedup, sessionization, top-N-per-group, slowly-changing dimensions, partition tricks. Writing the shapes by hand turns the unfamiliar into pattern recognition

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