Instacart Interview Questions (4+ Questions)

Last Updated: June 8, 2026 • 4 QuestionsReal Company Interviews

Prepare for your Instacart interview with our comprehensive collection of 4+ real interview questions and detailed answers. These questions have been curated from actual Instacart technical interviews across various roles including DevOps Engineer, Data Engineer, QA Engineer, and more.

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Interview Questions
1
Categories
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Difficulty Levels

Table of Contents

Our Instacart interview questions cover a wide range of technical topics and difficulty levels, from entry-level positions to senior roles. Each question includes detailed explanations and answers to help you understand the concepts and prepare effectively for your interview.

💡 Pro Tips for Instacart Interviews

  • Practice each question and understand the underlying concepts
  • Review Instacart's specific technologies and methodologies
  • Prepare follow-up questions and edge cases
  • Practice explaining your solutions clearly and concisely

Interview Questions & Answers

1. Cheapest Flights Within K Stops

Company: Instacart Difficulty: medium Categories: Devops, Data engineering

def find_cheapest_price(n: int, flights: list[list[int]], src: int, dst: int, k: int) -> int:
prices = [float("inf")] * n
prices[src] = 0

for i in range(k + 1):
    temp_prices = prices.copy()
    
    for u, v, w in flights:
        if prices[u] != float("inf") and prices[u] + w < temp_prices[v]:
            temp_prices[v] = prices[u] + w
            
    prices = temp_prices
    
return prices[dst] if prices[dst] != float("inf") else -1

2. Self-Join for Duplicate Email Detection

Company: Instacart Difficulty: easy 🔒 Premium Categories: Data analysis, Data engineering

When preparing for a technical interview, you may encounter questions that test your ability to manipulate and query databases using SQL. One such common question is:

Objective

Retrieve all email addresses that appear more than once in the Customers table. The result should list each duplica...


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3. Decompose Time-Series Data into Trend, Seasonal, and Residual Components

Company: Instacart Difficulty: medium Categories: Data analysis, Data engineering

Use Python statsmodels to decompose daily temperature time-series data into trend, seasonal, and residual components, saving each component to separate CSV files.

4. Corrected Order Pairing

Company: Instacart Difficulty: medium Categories: Data engineering

SELECT
CASE
WHEN order_id % 2 != 0
AND order_id = (
SELECT
MAX(order_id)
FROM
orders
) THEN order_id
WHEN order_id % 2 != 0 THEN order_id + 1
ELSE order_id - 1
END AS corrected_order_id,
item
FROM
orders
ORDER BY
corrected_order_id;


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