just finished a 4-round data engineer loop at instacart. thought i'd drop notes while things are still fresh because i couldn't find much specific info before going in.
the recruiter screen was pretty standard. 30 min, talked about my background, they explained the eng hiring bar and leveling. nothing technical.
round 1: SQL + data modeling big focus here. they gave me a scenario based on something like order lifecycle data (think: orders, deliveries, items, zones). they wanted me to write queries to surface anomalies and then design a schema that could handle real-time updates without locking. i'd say intermediate-hard SQL difficulty. window functions came up. partitioning logic. definitely brush up on RANK() vs DENSE_RANK() and running totals.
round 2: pipeline design this one was more system-design-ish. we talked about ingesting high-volume event streams (think Kafka) into a warehouse (they're on Redshift from what i could tell, though didn't confirm). they cared a lot about idempotency, late-arriving data, and how i'd handle schema evolution over time. CDC patterns came up. i mentioned dbt for transformations and they seemed comfortable with that world.
round 3: coding one question, pure python, working with a dataframe-style dataset. not leetcode-style, more like "here's messy data, clean it and compute X." pandas knowledge helped a lot. they cared about whether i could articulate edge cases without being prompted.
round 4: behavioral standard STAR format. questions around ambiguity, cross-functional conflict, dealing with bad data upstream. they asked specifically about a time i had to push back on a product requirement because of data infrastructure limitations. have a story ready for that one.
overall the process felt well-run. two weeks from first screen to final answer. i'm at 7 YOE and was targeting L5 equivalent. the caliber of interviewers was solid, they clearly use their own stack day-to-day.
would answer follow-up questions, happy to.