
HCL Technologies Software Engineer interviews reported by candidates combine screening or aptitude, technical discussions, project deep-dives, and HR or communication evaluation. Prepare core programming, SQL, your stated stack, and a clear project narrative.
$105K
Avg. Base Comp
$130K
Avg. Total Comp
3-5 rounds
Typical Rounds
1-2 weeks
Process Length
HCL Technologies Software Engineer candidates describe several routes into the process, including online assessments and campus-style flows with aptitude or group discussion before technical and HR conversations. Project discussion is the most consistent thread: candidates were asked to explain what they built, their individual contribution, technology choices, challenges, and the reasoning behind design decisions. Several reports also describe follow-up questions tied directly to the candidate’s résumé.
Technical emphasis varied with the candidate’s background. Java-oriented interviews included OOP, collections, multithreading, Spring Boot, JPA, SQL, Linux, and basic DSA. Frontend-oriented reports included HTML, CSS, React, and JavaScript concepts such as promises, callbacks, closures, copying objects, and destructuring. Other candidates encountered string manipulation, character-frequency counting, a stack problem, SQL questions, or broad MCQ-based assessments. Prepare the fundamentals of the language and stack shown on your résumé rather than assuming every interview follows one technical template.
Communication may be assessed through HR or a group discussion. Practice a concise introduction, walk through one project end to end, and explain your choices aloud while solving a basic coding problem. The supplied reports differ in sequence, so the hiring route and technical focus may shape the final format.
Synthesized from 14 candidate reports by our editorial team.
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Real interview reports from people who went through the Hcl Technologies process.
The process was pretty straightforward and moved fast, but it still felt a little inconsistent in what they emphasized. I had one screening round first, then a technical interview, and after that it went to HR. The whole thing was virtual and wrapped up in about 10 to 12 days, which I appreciated because there wasn’t much waiting around between stages. In the screening, they kept it basic and checked communication, attitude, and whether I was willing to learn. The technical round was more about core engineering fundamentals than anything deeply advanced. I was asked a mix of basic programming MCQs, a SQL program, and one coding question in my language of choice. There was also a communication round in the process, which felt more like they were checking how clearly I could explain my thinking than testing any hard technical skill.
What stood out to me was that they seemed to care a lot about memorized concepts and standard answers. I got questions on Java, Spring Boot, streams, database basics, and project discussion, plus a simple DSA-style problem around target sum pairs. There was also a design question, but nothing too heavy. Overall, I’d call the difficulty easy to moderate, mostly because the questions were direct and familiar rather than tricky. My biggest surprise was that even though the interview felt like it went well, the outcome wasn’t guaranteed. I was also asked a behavioral question about my biggest weakness and what I need to correct, so they did include HR-style evaluation alongside the technical parts. In the end, I didn’t get an offer from this process, even though it felt smooth on the surface. My takeaway is to be ready for very basic coding, SQL, and Java/Spring fundamentals, and to answer project and behavioral questions crisply without overcomplicating them.
Prep tip from this candidate
Be ready for basic programming MCQs, a SQL coding question, and a simple DSA problem like target sum pairs. Also review Java, Spring Boot, streams, and database fundamentals, since the technical round seemed to lean heavily on those core topics.
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Sourced from candidate reports and verified by our team.
Topics based on recent interview experiences.
Featured question at Hcl Technologies
Given two sorted lists, write a function to merge them into one sorted list.
| Question | |
|---|---|
| Tower of Hanoi | |
| Concurrent LLM Serving | |
| VLAN 2 Connectivity Issue | |
| Client Solution Pushback | |
| 2nd Highest Salary | |
| Top Three Salaries | |
| Empty Neighborhoods | |
| Employee Salaries | |
| Closest SAT Scores | |
| Subscription Overlap | |
| Monthly Customer Report | |
| Prime to N | |
| Top 3 Users | |
| Random SQL Sample | |
| Largest Salary by Department | |
| String Shift | |
| Rolling Bank Transactions | |
| Customer Orders | |
| Find the Missing Number | |
| Comments Histogram | |
| Raining in Seattle | |
| Find the First Non-Repeating Character in a String | |
| Bagging vs Boosting | |
| Retailer Data Warehouse | |
| Size of Joins | |
| Minimum Change | |
| Upsell Transactions | |
| Lowest Paid | |
| Level Of Rain Water In 2D Terrain |
Synthesized from candidate reports. Individual experiences may vary.
Candidates report that the opening stage may be an online assessment or a brief screen. Reported assessments included programming MCQs, SQL, simple coding, aptitude, verbal reasoning, and communication checks; one account described a short Teams conversation that moved from self-introduction into technical questions.
Technical discussions may cover Java, OOP, SQL, Spring Boot, JavaScript, HTML/CSS, arrays, strings, or basic DSA. Candidates also reported practical questions such as character-frequency counting, palindrome or reverse-number checks, target-sum pairs, and database fundamentals rather than uniformly advanced algorithms.
Several candidates report detailed questions about projects: their contribution, chosen technologies, API handling, testing, production failures, traffic, performance, and design decisions. Prepare to explain one project clearly and answer follow-ups that connect its implementation to the skills on your résumé.
Candidates report a final HR or communication-focused conversation in some processes, while others also encountered group discussion or an AI communication round. Topics may include behavioral questions, expectations, relocation, salary, willingness to learn, and how clearly you explain your thinking.