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Instacart interview notes, page 6 of 13

Large Enterprises

Most of these Instacart write-ups come from Software Engineers (88), then Data Scientists (28) and Machine Learning Engineers (5). The most reported rounds are the technical phone screen (93), the system design round (13), the behavioral / leadership round (6) and the product sense round (6).

128 interview notes · updated Jul 2026

Instacart·Software Engineer·Technical Phone Screen

May 2026
Instacart coding screen, pretty focused on data manipulation and some light system design thinking. The problem itself wasn't crazy hard but the edge cases tripped me up a bit.
  • Implement a method that returns the top N employees who have accumulated the most total time in the office.

“Went straight to a max-heap and sorted by total duration per worker.”

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Instacart·Software Engineer·Hiring Manager Screen

May 2026
Interviewed for a bizops role at Instacart. One behavioral question, pretty focused on analytical thinking and how you connect data to actual decisions.
  • Walk me through a time you used data to identify and fix a problem.

“I had a decent story ready but I spent too long on the diagnosis part and barely got to what actually changed because of it.”

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Instacart·Software Engineer·Technical Phone Screen

May 2026
Coding round at Instacart for a software engineer role, pretty much one meaty design-plus-implementation question that took the whole session. The problem felt straightforward at first but the follow-ups on edge cases and streaming kept coming.
  • Build a simple banking system that supports multiple accounts with initial balances. Implement deposit, withdraw, and transfer operations, where each operation returns whether it succeeded. Reject any operation that would overdraw an account or reference an account that doesn't exist. Write a function that takes a sequence of operations and returns the final balances.
  • What edge cases would you handle in this banking system, such as zero or negative amounts, or a very large number of accounts?
  • Walk through the time and space complexity of your solution.
  • If operations arrive as a continuous stream rather than a batch, how would you process them efficiently?

“I started with a plain hash map keyed by account ID and that part was fine.”

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Instacart·Software Engineer·Technical Phone Screen

May 2026
Instacart software engineer interview with a SQL pivot problem that also had a Java implementation angle. The constraint about no external date libraries felt a bit artificial but whatever, it is what it is.
  • You have an orders table with columns like order_id, shopper_id, order_date, and status. Write a query or Java solution to pivot the data so each row represents one shopper and each column shows how many orders they have per status (e.g., DELIVERED, CANCELED, RETURNED). The solution should also work without any external date-parsing libraries.

“The SQL pivot part was fine, conditional aggregation with CASE WHEN is pretty standard.”

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Instacart·Software Engineer·Technical Phone Screen

May 2026
Instacart software engineer interview focused on a task management system, basically a mini CRUD + ranking problem. Pretty reasonable scope for a coding round, though the details around tie-breaking and edge cases were where things got interesting.
  • Design and implement a task management system with ADD_TASK, UPDATE_TASK, DELETE_TASK, GET_TASK, and TOP_K operations. ADD_TASK should return false if the task ID already exists, and TOP_K should return the top k tasks by priority with ties broken alphabetically by task ID.

“The CRUD part was fine, just a dict keyed by task_id and you're mostly done.”

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Instacart·Data Scientist·Technical Phone Screen

May 2026
Interviewed for a Data Scientist role at Instacart. The whole thing basically came down to one big case-style question that you had to walk through end to end, which sounds manageable until you realize how many layers they expect you to cover.
  • Walk me through a high-stakes business problem you solved using data. Cover the decision you were trying to inform, the hypotheses you formed, how you defined success, who the stakeholders were, what data you used, how you designed the analysis or experiment, how you handled confounders or missing data, how you validated the result, and what the measurable impact was. Also name one thing you'd do differently.

“This is basically a full case study crammed into one question and I underestimated how much they wanted on the validation piece specifically.”

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Instacart·Software Engineer·Technical Phone Screen

May 2026
Instacart SWE phone screen, pretty much just one meaty scheduling problem with a couple of follow-ups tacked on. The core question wasn't too bad but the follow-ups pushed into territory I hadn't really prepared for.
  • Given n customer orders each with an arrival time and a preparation time, simulate a single chef processing orders non-preemptively. When the chef is idle and multiple orders are waiting, they take the one that arrived earliest. Compute the average waiting time across all customers, where waiting time is defined as finish time minus arrival time.
  • If you could freely choose the order in which waiting orders are processed (rather than strictly earliest-arrival first), how would you minimize the average waiting time?
  • Generalize the scheduling problem to k chefs working in parallel. Describe your algorithm and its time complexity.

“Sorted by arrival time first, then simulated a current-time pointer to track when the chef finishes each order.”

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Instacart·Data Scientist·Onsite - Cross-functional / Panel

May 2026
Instacart data scientist interview with a pretty brutal prioritization scenario, the kind where there's no clean answer and they're clearly watching how you think under pressure rather than whether you land on the 'right' framework.
  • You have three deliverables all due this Friday: the CFO wants a revenue forecast update, a PM needs an experiment readout before a Monday launch decision, and Ops has escalated a P0 data quality issue that's breaking dashboards. You have 8 hours and no one to delegate to. Walk through how you'd prioritize, what sequence you'd follow, what you'd drop or push back on, and what you'd actually say to each stakeholder.

“This one took me a minute to even parse.”

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Instacart·Data Scientist·Technical Phone Screen

May 2026
Instacart data scientist interview with a tricky A/B testing scenario where the north star metric moves in the wrong direction but a secondary metric looks good. Forces you to think carefully about what you actually care about optimizing.
  • An experiment increases average order volume but decreases profit per order (the north star metric). Do you launch? Walk through your decision process.

“This one tripped me up because the instinct is to get excited about higher order volume and rationalize the rest.”

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Instacart·Backend Engineer·Technical Phone Screen

May 2026
Instacart backend engineer interview, got a debugging/implementation problem centered on a search filter that was returning unfiltered results. Pretty reasonable problem once you slow down and read all the edge cases carefully.
  • You're given a broken book catalog search endpoint that returns the entire catalog regardless of what the user types. Implement the backend filtering function so it correctly returns only books whose title, author, or tags contain the query string (case-insensitive, trimmed), with an optional availability filter.

“The core logic isn't hard but I almost tripped on the empty query case.”

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