Shopify data engineering interview questions are SQL end-to-end with a sharp merchant-sessions analytics edge: five SQL primitives ( DATE_TRUNC('month', session_ts) + COUNT(*) for monthly session rollups, DATE_TRUNC('day', session_ts) + COUNT(*) for daily session counts, JOIN of shops to MIN(session_ts) GROUP BY shop_id with date-difference for activation latency, AVG(sessions) OVER (PARTITION BY shop_id ORDER BY day ROWS BETWEEN 6 PRECEDING AND CURRENT ROW) for trend-smoothed rolling traffic, and SUBSTRING(url FROM 'utm_source=([^&]+)') regex for marketing-attribution source extraction). The framings are merchant data—shop sessions, daily and monthly traffic, activation funnels, smoothed traffic trends, and UTM-tagged landing-URL analytics. This guide walks through the five topic clusters Shopify actually tests, each with a detailed topic explanation , per-sub-topic explanation with a worked example and its solution , and an interview-style problem with a full solution that explains why it works.…