Interview experience
Nagarro Interview Questions and Answers (2026)
Overview
Section titled “Overview”Nagarro’s fresher process is unusually coding-heavy for an IT-services firm - two separate coding-focused written rounds, one often done on paper, before the technical interview even starts.
Nagarro interview process at a glance
Section titled “Nagarro interview process at a glance”| Round | Duration | What they test |
|---|---|---|
| Written Test | 60-90 min | Aptitude, CS/domain MCQs, 3 coding problems |
| Coding Round | 45-60 min | 3-4 coding problems, often pen-and-paper |
| Technical Interview | 30-45 min | Code optimization, DS/algorithms/SQL |
| HR Interview | 20-30 min | Fit, offer discussion |
Written Test
Section titled “Written Test”Combines standard aptitude (quant, logical, verbal) with technical MCQs spanning OS, data structures, algorithms, C, Java, SQL, and networking, plus 3 coding problems in the same sitting.
Common questions
- Quantitative and logical aptitude - the standard campus-screen mix
- MCQs on OS, DS, algorithms, and networking fundamentals
- 3 coding problems - typically array/string manipulation and basic logic building
- SQL query MCQs or short-answer questions
Coding Round
Section titled “Coding Round”A second, distinct written round - often literally pen-and-paper - with 3-4 more coding problems. Nagarro is explicit that this round prioritizes algorithmic thinking and correct logic over clean, compiler-ready syntax, since you’re not typing it into an IDE.
Common questions
- Solve 3-4 coding problems by hand, showing your logic clearly even without running the code
- Array, string, and basic recursion problems
- Problems that reward a clear, step-by-step approach over a “clever” one-liner
- Explain your algorithm’s time complexity without running it
Technical Interview
Section titled “Technical Interview”Rather than starting fresh, this round typically revisits the code you wrote in the Coding Round and asks you to walk through, defend, and optimize it - alongside further DS/algorithms/SQL questions.
Common questions
- Optimize the code you wrote in the earlier coding round - what would you change and why?
- Explain the time/space complexity of your written solution
- Additional DS/algorithms questions building on what you’ve already shown
- SQL queries involving joins or aggregate functions
Round-by-round accounts are on the Nagarro interview experience page.
HR Interview
Section titled “HR Interview”A closing round on fit, motivation, and offer discussion.
Common questions
- Tell me about yourself and why Nagarro
- The technical round often asks you to optimize code you wrote earlier - tell me about a time you improved a solution you’d already built
- Nagarro describes its culture as non-hierarchical, with engineers taking direct ownership - how do you feel about that kind of autonomy?
- Are you open to relocating to Gurugram, Jaipur, Bengaluru, or Hyderabad?
Sample answer frameworks for each of these are on the Nagarro HR interview questions page.
Why two coding rounds before the interview
Section titled “Why two coding rounds before the interview”Most IT-services companies run a single OA and reserve coding assessment for that one sitting. Nagarro instead splits it across the Written Test and a dedicated Coding Round, with the second one commonly done on paper - a deliberate signal that Nagarro cares about your ability to reason through a problem correctly under low-tooling conditions, not just produce working code in an IDE with autocomplete. If you’re used to prepping purely on LeetCode with a compiler running, practice writing out full solutions by hand as part of your prep.
Common technical interview questions and answers
Section titled “Common technical interview questions and answers”Q: Reverse a linked list - what is the iterative approach and its complexity?
Keep three pointers: prev (initially null), curr (initially head), and next. In each iteration store next = curr.next, point curr.next back to prev, then advance prev = curr and curr = next. When curr becomes null, prev is the new head. This runs in O(n) time and O(1) extra space, which is why interviewers prefer it over the recursive version that costs O(n) stack space.
Q: How do you find the second largest element in an array in a single pass?
Track two variables, largest and secondLargest, both initialised to negative infinity. For each element: if it is greater than largest, set secondLargest = largest and largest = element; else if it is greater than secondLargest and not equal to largest, set secondLargest = element. One pass gives O(n) time and O(1) space. Sorting also works but costs O(n log n), so mention the single-pass version first and handle the edge case where all elements are identical.
Q: Write a SQL query to find the second highest salary from an Employee table.
A portable version is SELECT MAX(salary) FROM Employee WHERE salary < (SELECT MAX(salary) FROM Employee). It returns NULL rather than erroring when every salary is identical. On MySQL 8 or PostgreSQL you can also use SELECT salary FROM (SELECT salary, DENSE_RANK() OVER (ORDER BY salary DESC) rnk FROM Employee) t WHERE rnk = 2. Use DENSE_RANK rather than ROW_NUMBER so tied top salaries do not shift the answer.
Q: What is the difference between an INNER JOIN and a LEFT JOIN?
INNER JOIN returns only rows where the join condition matches in both tables, so unmatched rows on either side disappear. LEFT JOIN returns every row from the left table and fills the right table’s columns with NULL where there is no match, so the result is at least as large as the left table. A common Nagarro follow-up is finding rows with no match: LEFT JOIN the two tables and add WHERE right_table.id IS NULL, which is the anti-join pattern.
Q: Explain deadlock and the four Coffman conditions.
A deadlock is a state where a set of processes are each blocked waiting on a resource held by another process in the set, so none can proceed. It requires all four Coffman conditions simultaneously: mutual exclusion (a resource is non-shareable), hold and wait (a process holds one resource while requesting another), no preemption (resources cannot be forcibly taken), and circular wait (a cycle exists in the wait-for graph). Breaking any single condition prevents deadlock - for example, imposing a global ordering on resource acquisition breaks circular wait.
Q: What is the time complexity of quicksort, and when does it degrade?
Average and best case are O(n log n) because a good pivot splits the array roughly in half at each of log n levels, with O(n) partitioning work per level. Worst case is O(n squared), which happens when the pivot is consistently the smallest or largest element - classically when you pick the first element as pivot on already-sorted input. Randomised pivot selection or median-of-three makes that worst case vanishingly unlikely; quicksort uses O(log n) stack space and is not stable, unlike merge sort’s O(n log n) guarantee with O(n) extra space.
Q: How would you detect a loop in a linked list without extra space?
Use Floyd’s cycle-detection algorithm: advance a slow pointer one node at a time and a fast pointer two nodes at a time. If they ever meet, a cycle exists; if fast reaches null, the list is acyclic. To find the start of the loop, reset one pointer to the head and move both one step at a time - they meet at the loop’s entry node. Time is O(n) and space is O(1), versus the hash-set approach that also runs in O(n) time but costs O(n) space.
Q: How do you check whether two strings are anagrams of each other?
If the lengths differ, return false immediately. Otherwise use a frequency count: for lowercase ASCII, a fixed 26-integer array, incrementing for the first string and decrementing for the second, then verifying every counter is zero. That is O(n) time and O(1) space since the array size is constant. Sorting both strings and comparing also works and is easier to write on paper, but costs O(n log n) - a good trade-off to state out loud in Nagarro’s pen-and-paper round.
Frequently asked questions about Nagarro interviews
Section titled “Frequently asked questions about Nagarro interviews”What is the Nagarro interview process for freshers?
Nagarro typically runs 4 rounds for freshers hired as Associate/Assistant System Engineers: 1. Written Test - aptitude (quant, logical, verbal) plus technical MCQs (OS, DS, algorithms, C, Java, SQL, networking) and 3 coding problems. 2. Coding Round - a second, often pen-and-paper, written round with 3-4 coding problems focused purely on problem-solving. 3. Technical Interview - discusses and asks you to optimize the code from the coding round, plus DS/algorithms/SQL questions. 4. HR Interview - fit and offer discussion.
What questions are asked in Nagarro interviews?
The written rounds mix aptitude with core CS MCQs (OS, DS, algorithms, SQL, networking) and coding problems. A distinctive part of Nagarro’s process is that the second coding round is often done on paper, and interviewers explicitly say they care about your algorithmic thinking and problem-solving approach, not clean pseudocode syntax. The technical interview usually revisits and asks you to optimize what you wrote in that round.
How many rounds are there in the Nagarro interview?
Most Nagarro drives run 4 rounds: a written test, a separate coding round, a technical interview, and an HR interview. The two coding-heavy rounds before the technical interview is the main thing that distinguishes Nagarro’s process from a typical single-OA pipeline.
Is Nagarro’s process similar to Coforge’s?
They’re often paired in prep guides since both are engineering-leaning IT services/product-engineering firms hiring from overlapping campus pools, and both weight coding more heavily than a mass-recruiter. But Nagarro leans more logic-and-coding-heavy overall - two separate coding-focused written rounds before the technical interview - whereas Coforge’s process opens with a distinct Communication Assessment gate that Nagarro doesn’t run. Prep quant/verbal enough to avoid easy losses either way, but prioritize logical reasoning and coding for Nagarro specifically.
How should I prepare for Nagarro interviews?
Practice writing correct, working code by hand (not just in an IDE), since Nagarro’s coding round is often pen-and-paper and prioritizes problem-solving logic over syntax polish. Revise core CS fundamentals (OS, DS, algorithms, SQL, networking) for the MCQ sections, and be ready to optimize your own code when asked in the technical interview.