Quick Overview

This question evaluates advanced SQL and data-engineering competencies such as cohort and retention analysis, deduplication, timezone normalization, last-touch attribution, aggregate revenue calculations, and effective use of window functions in the Data Manipulation (SQL/Python) domain.

Write complex SQL for cohorts and retention

Company: TikTok

Role: Software Engineer

Category: Data Manipulation (SQL/Python)

Difficulty: medium

Interview Round: Technical Screen

Given tables users(uid, created_at, country), orders(order_id, uid, amount, created_at, status), and events(uid, ts, event_type, campaign), write one SQL query that outputs, for each month and country: ( 1) new users, ( 2) conversion rate within 7 days of signup, ( 3) 7-day rolling retention (active on day D and again on D+ 7), ( 4) GMV excluding refunded/canceled orders, and ( 5) top campaign by last-touch attribution from events. Handle late-arriving events, deduplicate by (uid, ts, event_type), ensure timezone consistency, and document window-function choices.

Quick Answer: This question evaluates advanced SQL and data-engineering competencies such as cohort and retention analysis, deduplication, timezone normalization, last-touch attribution, aggregate revenue calculations, and effective use of window functions in the Data Manipulation (SQL/Python) domain.

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