Zillow, a leading online real estate marketplace, is renowned for its innovative approach to technology and data. Securing a software engineering role, whether as an intern or a full-time engineer, requires demonstrating robust technical skills, particularly in algorithms and data structures. The Zillow software engineering interview process is comprehensive, often involving multiple rounds that assess problem-solving abilities through LeetCode-style coding challenges, system design discussions, and behavioral questions. Preparing effectively for these technical interviews is paramount, as Zillow seeks engineers who can not only write efficient code but also think critically about complex problems. This guide provides a curated overview of common Zillow Software Engineering LeetCode interview questions and themes, offering insights into how to approach them strategically to maximize your chances of success. Understanding the types of problems frequently encountered, alongside a structured preparation approach, will significantly enhance your performance in these highly competitive interviews.
What Are Zillow Software Engineering LeetCode Interview Questions?
Zillow Software Engineering LeetCode interview questions are algorithmic coding challenges typically found on platforms like LeetCode, designed to evaluate a candidate's proficiency in data structures, algorithms, and problem-solving. These questions range in difficulty from easy to hard, with a strong emphasis on medium-level problems during Zillow's technical screens and onsite rounds. Interviewers use these questions to gauge a candidate's ability to translate a real-world problem into an algorithmic solution, write clean and efficient code, analyze time and space complexity, and handle various edge cases. The topics span core computer science concepts such as arrays, strings, trees, graphs, dynamic programming, and sorting/searching. Success in these rounds requires not just finding a correct solution but also demonstrating a clear thought process, explaining design choices, and optimizing for performance. They mimic the analytical thinking required daily in software development roles at Zillow.
Why Do Interviewers Ask Zillow Software Engineering LeetCode Interview Questions?
Interviewers at Zillow ask LeetCode-style questions for several critical reasons. Primarily, they serve as a standardized method to assess a candidate's foundational computer science knowledge and their ability to apply it. These problems reveal how candidates approach abstract challenges, break them down into manageable parts, and construct logical, efficient solutions. They evaluate critical thinking, debugging skills, and the capacity to innovate under pressure. Furthermore, these questions help interviewers understand a candidate's coding style, their proficiency in a chosen programming language, and their ability to communicate complex technical ideas effectively. Zillow looks for engineers who can not only solve problems but also articulate their thought process and justify their design decisions. This holistic evaluation ensures that hired engineers possess the analytical rigor and practical coding skills necessary to contribute effectively to Zillow's complex, data-driven platforms.
Preview List
How do you find the two numbers in an array that sum up to a target value?
How do you check if a given string is a palindrome, ignoring non-alphanumeric characters?
How do you balance parentheses in a given string?
How do you search for a target value in a 2D matrix where rows and columns are sorted?
How do you find the nth Fibonacci number using dynamic programming?
How do you merge overlapping intervals in a list?
How do you perform a Breadth-First Search (BFS) on a binary tree?
How do you implement a stack using two queues?
How do you detect a cycle in a linked list?
How do you find the longest substring without repeating characters?
How do you rotate an image represented by an N x N 2D matrix by 90 degrees clockwise?
How do you calculate the minimum number of coins to make a given amount?
How do you find the lowest common ancestor (LCA) of two nodes in a binary tree?
How do you check if a binary tree is symmetric?
How do you find all anagrams of a pattern string in a text string?
How do you implement a queue using two stacks?
How do you find the median of two sorted arrays?
How do you invert a binary tree?
How do you determine if a given graph is a valid tree?
How do you find the maximum subarray sum?
How do you implement pow(x, n) (x raised to the power n)?
How do you remove Nth node from end of list?
How do you count the number of islands in a 2D binary grid?
How do you find the maximum depth of a binary tree?
How do you climb stairs, given you can climb 1 or 2 steps at a time, to reach the top?
How do you serialize and deserialize a binary tree?
How do you find a path in a grid from top-left to bottom-right?
How do you find the product of all elements except self in an array?
How do you determine if a string can be segmented into a space-separated sequence of dictionary words?
How do you find the number of connected components in an undirected graph?
1. How do you find the two numbers in an array that sum up to a target value?
Why you might get asked this:
Tests basic array manipulation, hash map usage for efficient lookups, and understanding of time/space complexity trade-offs. It's a foundational problem.
How to answer:
Use a hash map to store numbers and their indices. Iterate through the array; for each number, check if target - current_number exists in the map.
Example answer:
Iterate the array. For each number x, calculate complement = target - x. If complement is in the hash map, return [map[complement], currentindex]. Otherwise, add x and currentindex to the map. Handles duplicates.
2. How do you check if a given string is a palindrome, ignoring non-alphanumeric characters?
Why you might get asked this:
Evaluates string manipulation, two-pointer technique, character validation, and case insensitivity. Practical for data cleaning.
How to answer:
Use two pointers, one at the start and one at the end. Move them inwards, skipping non-alphanumeric characters. Compare characters after converting to lowercase.
Example answer:
Initialize left and right pointers. While left < right, advance pointers past non-alphanumeric chars. If s[left].lower() != s[right].lower(), return false. Increment left, decrement right. Return true.
3. How do you balance parentheses in a given string?
Why you might get asked this:
Assesses stack data structure understanding and its application in validating nested structures. Essential for parsing expressions.
How to answer:
Use a stack. Push opening brackets onto the stack. When a closing bracket is encountered, pop from the stack and check for a match.
Example answer:
Initialize an empty stack and a map for bracket pairs. Iterate string: if open, push; if close, pop and check match with map. If mismatch or empty stack, return false. Finally, stack must be empty.
4. How do you search for a target value in a 2D matrix where rows and columns are sorted?
Why you might get asked this:
Tests ability to adapt search algorithms to multi-dimensional data structures. Highlights optimized searching techniques beyond simple iteration.
How to answer:
Start from the top-right corner. If the current element is less than the target, move down; if greater, move left. This reduces the search space.
Example answer:
Start row = 0, col = matrix[0].length - 1. While row < matrix.length and col >= 0: if matrix[row][col] == target, return true. Else if matrix[row][col] < target, row++. Else col--. Return false.
5. How do you find the nth Fibonacci number using dynamic programming?
Why you might get asked this:
A classic DP problem. Checks understanding of memoization/tabulation, recursion with optimization, and avoiding redundant computations.
How to answer:
Use an array to store previously computed Fibonacci numbers (memoization) or build up from base cases (tabulation) to avoid exponential time complexity.
Example answer:
Create a DP array dp of size n+1. Set dp[0]=0, dp[1]=1. Iterate from i=2 to n, setting dp[i] = dp[i-1] + dp[i-2]. Return dp[n].
6. How do you merge overlapping intervals in a list?
Why you might get asked this:
Tests sorting algorithms and greedy approaches. Common in scheduling and resource allocation problems.
How to answer:
Sort the intervals by their start times. Iterate through the sorted intervals, merging current with the next if they overlap.
Example answer:
Sort intervals by start time. Initialize merged = [first_interval]. Iterate remaining intervals: if current overlaps with last in merged, update merged.last.end = max(merged.last.end, current.end). Else, add current to merged.
7. How do you perform a Breadth-First Search (BFS) on a binary tree?
Why you might get asked this:
Assesses fundamental graph/tree traversal algorithms. Important for level-order traversal and shortest path problems.
How to answer:
Use a queue. Add the root to the queue. While the queue is not empty, dequeue a node, process it, and enqueue its left and right children.
Example answer:
Initialize a queue with the root. While the queue isn't empty, node = queue.dequeue(). Process node.val. If node.left exists, queue.enqueue(node.left). If node.right exists, queue.enqueue(node.right).
8. How do you implement a stack using two queues?
Why you might get asked this:
Tests understanding of ADT implementations and creative use of one data structure to mimic another.
How to answer:
Use two queues, q1 and q2. For push, add new element to q1. For pop, move all but the last element from q1 to q2, then dequeue the last element from q1. Swap q1 and q2.
Example answer:
push(x): q1.enqueue(x). pop(): while q1.size > 1, q2.enqueue(q1.dequeue()). res = q1.dequeue(). Swap q1, q2. Return res. top() is similar, just peek.
9. How do you detect a cycle in a linked list?
Why you might get asked this:
A classic pointer manipulation problem. Tests ability to handle linked list structures and clever algorithmic solutions.
How to answer:
Use Floyd's Cycle-Finding Algorithm (tortoise and hare). One pointer moves one step at a time, the other moves two. If they meet, a cycle exists.
Example answer:
Initialize slow = head, fast = head. While fast and fast.next exist: slow = slow.next, fast = fast.next.next. If slow == fast, a cycle exists, return true. Return false.
10. How do you find the longest substring without repeating characters?
Why you might get asked this:
Tests sliding window technique and hash map usage for character tracking. Common for string processing tasks.
How to answer:
Use a sliding window defined by two pointers (left, right) and a hash set to track characters within the current window.
Example answer:
left=0, maxLength=0, charSet=set(). Iterate right from 0: While s[right] in charSet, charSet.remove(s[left++]). Add s[right] to charSet. maxLength = max(maxLength, right - left + 1).
11. How do you rotate an image represented by an N x N 2D matrix by 90 degrees clockwise?
Why you might get asked this:
Tests matrix manipulation and in-place algorithms. Requires careful index tracking and understanding of transformations.
How to answer:
First, transpose the matrix (swap matrix[i][j] with matrix[j][i]). Then, reverse each row. This performs a 90-degree clockwise rotation.
Example answer:
For i from 0 to n-1, for j from i to n-1, swap matrix[i][j] with matrix[j][i] (transpose). Then, for each row, reverse its elements.
12. How do you calculate the minimum number of coins to make a given amount?
Why you might get asked this:
A classic dynamic programming problem. Checks optimization, state definition, and base cases.
How to answer:
Use a DP array where dp[i] is the minimum coins for amount i. Iterate through amounts, considering each coin denomination.
Example answer:
Initialize dp array of size amount+1 with infinity, dp[0]=0. For each coin in coins: for i from coin to amount: dp[i] = min(dp[i], dp[i-coin] + 1). Return dp[amount] or -1 if infinity.
13. How do you find the lowest common ancestor (LCA) of two nodes in a binary tree?
Why you might get asked this:
Tests recursive thinking, tree traversal, and understanding of node relationships in a tree structure.
How to answer:
Recursively search for p or q. If a node is an ancestor to both (one in left subtree, one in right), or matches one and is ancestor to other, it's the LCA.
Example answer:
Base case: if root is null, p, or q, return root. Recursively call on left and right children. If both left and right calls return non-null, current root is LCA. Else, return non-null result from left or right.
14. How do you check if a binary tree is symmetric?
Why you might get asked this:
Tests recursive pattern recognition and understanding of tree mirroring. Key for verifying structural properties.
How to answer:
Use a helper function that takes two nodes and checks if they are mirrors of each other (i.e., node1.left matches node2.right and node1.right matches node2.left).
Example answer:
Define isMirror(t1, t2): if both null, true; if one null, false; if t1.val != t2.val, false. Return isMirror(t1.left, t2.right) && isMirror(t1.right, t2.left). Call isMirror(root.left, root.right).
15. How do you find all anagrams of a pattern string in a text string?
Why you might get asked this:
Combines sliding window with frequency counting (hash maps or arrays). Efficiently finds permutations.
How to answer:
Use a sliding window. Maintain character counts for the pattern and the current window. Expand window, update counts; shrink window from left, update counts. Compare counts.
Example answer:
Create char frequency maps for p and initial window of s (length p). Iterate s with sliding window: remove char leaving window, add char entering window. If maps match, record start index.
16. How do you implement a queue using two stacks?
Why you might get asked this:
Tests understanding of ADT implementations and creative use of one data structure to mimic another, similar to stack using queues.
How to answer:
Use two stacks: inStack for push operations and outStack for pop/peek. When popping/peeking, if outStack is empty, transfer all elements from inStack to outStack.
Example answer:
push(x): inStack.push(x). pop(): if outStack empty, while inStack not empty, outStack.push(inStack.pop()). Return outStack.pop(). peek() is similar, just peek instead of pop.
17. How do you find the median of two sorted arrays?
Why you might get asked this:
A challenging problem that tests binary search, array partitioning, and handling edge cases with arrays of different lengths.
How to answer:
Use a binary search approach on the smaller array to find a partition point such that combining both arrays' partitioned parts yields the correct median.
Example answer:
Perform binary search on the partition of the smaller array. Calculate corresponding partition in larger array. Check if max(leftpart) of both arrays is <= min(rightpart) of both. Adjust partition based on this.
18. How do you invert a binary tree?
Why you might get asked this:
Tests recursive tree traversal and simple manipulation of node pointers. A warm-up for more complex tree problems.
How to answer:
Recursively traverse the tree. At each node, swap its left and right children.
Example answer:
Base case: if root is null, return null. Swap root.left and root.right. Recursively call invertTree(root.left) and invertTree(root.right). Return root.
19. How do you determine if a given graph is a valid tree?
Why you might get asked this:
Tests graph traversal (DFS/BFS) and cycle detection. A tree is a connected graph with no cycles.
How to answer:
Perform a DFS or BFS traversal. During traversal, keep track of visited nodes and parent nodes. If you encounter an already visited node that isn't the direct parent, a cycle exists. Also, ensure all nodes are connected.
Example answer:
Use DFS with a visited set and a parent tracking. If dfs(node, parent) visits neighbor and neighbor is in visited and neighbor != parent, then a cycle exists. After DFS, check if all nodes are visited.
20. How do you find the maximum subarray sum?
Why you might get asked this:
A classic dynamic programming or greedy approach problem (Kadane's algorithm). Tests optimization and handling negative numbers.
How to answer:
Use Kadane's algorithm: maintain a currentmax ending at current position and a globalmax. currentmax = max(num, currentmax + num).
Example answer:
Initialize maxsofar = nums[0], currentmax = nums[0]. Iterate from i=1: currentmax = max(nums[i], currentmax + nums[i]). maxsofar = max(maxsofar, currentmax). Return maxsofar.
21. How do you implement pow(x, n) (x raised to the power n)?
Why you might get asked this:
Tests recursive thinking, handling edge cases (negative n, n=0), and optimization using binary exponentiation.
How to answer:
Handle n=0 and negative n. Use recursion and x^(2k) = (x^k)^2 property for efficient calculation.
Example answer:
If n=0, return 1. If n < 0, x = 1/x, n = -n. Recursively call half = myPow(x, n/2). If n is even, return half half. If n is odd, return half half * x.
22. How do you remove Nth node from end of list?
Why you might get asked this:
Tests linked list manipulation, handling edge cases (first/last node removal), and using two pointers (fast/slow).
How to answer:
Use two pointers. Move the first pointer n steps ahead. Then move both pointers simultaneously until the first pointer reaches the end. The second pointer will be at the node before the one to be removed.
Example answer:
Create a dummy node. Initialize first = dummy, second = dummy. Advance first n+1 times. Then, advance both first and second until first is null. second.next = second.next.next. Return dummy.next.
23. How do you count the number of islands in a 2D binary grid?
Why you might get asked this:
Classic graph traversal problem on a grid. Tests DFS/BFS application, matrix manipulation, and avoiding re-counting.
How to answer:
Iterate through the grid. If a '1' is found, increment island count and start a DFS/BFS from that point, marking all connected '1's as visited ('0').
Example answer:
Initialize count=0. Loop r and c: if grid[r][c] == '1', increment count, then perform DFS/BFS starting at (r,c) to turn all connected '1's to '0's. Return count.
24. How do you find the maximum depth of a binary tree?
Why you might get asked this:
A fundamental tree recursion problem. Tests understanding of tree structure and recursive traversal.
How to answer:
Recursively calculate the depth of the left and right subtrees. The maximum depth of the tree is 1 (for the root) plus the maximum of the left and right subtree depths.
Example answer:
Base case: if root is null, return 0. Return 1 + max(maxDepth(root.left), maxDepth(root.right)). This covers the recursive definition.
25. How do you climb stairs, given you can climb 1 or 2 steps at a time, to reach the top?
Why you might get asked this:
A classic dynamic programming problem, essentially Fibonacci. Tests DP formulation and recurrence relations.
How to answer:
Recognize this as a variation of the Fibonacci sequence. The number of ways to reach step n is the sum of ways to reach n-1 and n-2.
Example answer:
Create a DP array dp of size n+1. dp[0]=1, dp[1]=1. Iterate i from 2 to n: dp[i] = dp[i-1] + dp[i-2]. Return dp[n].
26. How do you serialize and deserialize a binary tree?
Why you might get asked this:
Tests tree traversal (e.g., pre-order), string manipulation, and handling null nodes for reconstruction. Complex but common.
How to answer:
For serialization, perform a traversal (e.g., pre-order), appending node values to a string, using a special marker for nulls. For deserialization, parse the string to reconstruct the tree recursively.
Example answer:
Serialize: DFS traversal, append node.val or 'N' for nulls, separated by commas. Deserialize: Split string by comma. Use queue of values. Reconstruct recursively, consuming values.
27. How do you find a path in a grid from top-left to bottom-right?
Why you might get asked this:
Tests graph traversal algorithms (DFS/BFS) on a grid, pathfinding, and handling obstacles/boundaries.
How to answer:
Use DFS or BFS. Explore neighbors (up, down, left, right), marking visited cells to avoid cycles. Stop when the bottom-right cell is reached.
Example answer:
Use DFS. Start at (0,0). Mark current cell visited. If (r,c) is target, return true. Explore valid neighbors: if isValid(nr, nc) and grid[nr][nc] is not obstacle and not visited, recursively call DFS. Backtrack.
28. How do you find the product of all elements except self in an array?
Why you might get asked this:
Tests array manipulation and optimizing for space/time complexity, avoiding division operator.
How to answer:
Make two passes. First pass computes prefix products. Second pass computes suffix products. Multiply them to get the result for each element.
Example answer:
Initialize result array with 1s. First pass: result[i] = product of elements before i. Second pass (from right): result[i] = result[i] * product of elements after i.
29. How do you determine if a string can be segmented into a space-separated sequence of dictionary words?
Why you might get asked this:
A classic dynamic programming or recursion with memoization problem. Tests string partitioning and dictionary lookups.
How to answer:
Use dynamic programming. dp[i] is true if s[0...i-1] can be segmented. dp[i] = dp[j] && wordDict.contains(s[j...i-1]) for 0 <= j < i.
Example answer:
dp array [false]*(len(s)+1), dp[0]=True. For i from 1 to len(s): for j from 0 to i-1: if dp[j] is true and s[j:i] is in wordDict, then dp[i]=True, break. Return dp[len(s)].
30. How do you find the number of connected components in an undirected graph?
Why you might get asked this:
Tests graph traversal (DFS/BFS) and understanding of connected components in graph theory.
How to answer:
Initialize a visited set. Iterate through all nodes. If a node is not visited, increment component count and start a DFS/BFS from it, marking all reachable nodes as visited.
Example answer:
Initialize components=0, visited=set(). For each node in graph: if node not in visited, components++. Perform DFS/BFS from node to mark all reachable nodes as visited. Return components.
Other Tips to Prepare for a Zillow Software Engineering LeetCode Interview
Beyond grinding through problems, effective preparation for Zillow's software engineering interviews requires a holistic approach. As Zillow seeks well-rounded engineers, focus not just on getting the correct answer but also on articulating your thought process clearly. "The only way to do great work is to love what you do," said Steve Jobs, and this passion translates into persistent, effective preparation. Practice explaining your solutions out loud, simulating the interview environment. Don't forget to revisit core computer science fundamentals, especially data structures like trees, graphs, and hash maps, and algorithms such as sorting, searching, and dynamic programming. For realistic practice, consider using Verve AI Interview Copilot to get instant feedback on your coding and communication. System design is crucial for Zillow roles; practice designing scalable, robust systems. Leverage tools like Verve AI Interview Copilot at https://vervecopilot.com to hone your behavioral responses, ensuring they align with Zillow's values of teamwork and innovation. Remember, "Success is not final, failure is not fatal: it is the courage to continue that counts," a quote often attributed to Winston Churchill. Utilize Verve AI Interview Copilot to polish your interview readiness across all facets.
Frequently Asked Questions
Q1: How difficult are Zillow LeetCode questions? A1: Mostly medium difficulty, occasionally easy or hard. Focus on common patterns in arrays, strings, trees, and dynamic programming.
Q2: Should I focus on a specific language for coding? A2: Zillow accepts most common languages (Python, Java, C++). Choose one you're most comfortable explaining and coding efficiently in.
Q3: Is system design always asked for software engineering roles? A3: For experienced software engineering roles, yes. For internships/new grad, it might be an easier version or not asked.
Q4: How important are behavioral questions? A4: Very important. Zillow emphasizes cultural fit and teamwork. Prepare STAR method answers for common scenarios like challenges and collaboration.
Q5: What resources are best for Zillow interview prep? A5: LeetCode (especially medium problems), Glassdoor/Interview Query for reported questions, and mock interview platforms like Verve AI Interview Copilot.
