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HashedIn by DeloitteSoftware Engineer
Updated Apr 1, 2026

HashedIn by Deloitte Software Engineer Interview Experiences 2026

Real, anonymous reports from people who interviewed for Software Engineer at HashedIn by Deloitte, newest first and distilled into what to expect across the loop.

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Hot & recentNewest first
7 months ago
Difficult Positive Pune

My interview journey for the SDE role at HashedIn by Deloitte followed a clean four-round arc. Round one was an online assessment where I solved coding and aptitude-style problems. Round two shifted into data structures and algorithms, and that was where they really checked how I reasoned through problems. Round three moved away from pure coding into system design, where I had to lay out a scalable architecture and walk through how the pieces fit together.

The final round was HR, focused on communication, behavioral topics, and cultural fit. Overall, the difficulty felt high—especially once it reached the DSA and system design stages—and I walked away without an offer. What stood out to me most was how each round seemed to raise the bar and test a different skill, rather than repeating the same style of questions. Even though I didn’t clear the process, the structure was clear and the expectations were consistent from one round to the next.
7 months ago

I went through a campus recruitment flow for a fresher SDE role at HashedIn by Deloitte, and it was framed as elimination-based throughout. The earliest step was resume shortlisting, where the initial form was filled through my institute’s TnP cell with basic details, and that determined who even got to the next stage.

After that, the process continued with multiple rounds, and each round worked like a filter—if I didn’t clear that stage, I wouldn’t move forward. That elimination vibe was consistent in how the flow was described to me: there wasn’t a lot of “keep going and recover” energy, it was more about passing each checkpoint.

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What to expect

Distilled from the reports

The Loop & Timeline

The interview process typically consists of an online assessment followed by multiple technical rounds and an HR discussion, often structured as an elimination process where each stage builds on the previous one. Candidates should expect a clear progression from coding assessments to deeper technical evaluations and finally to behavioral fit discussions.

EliminationStructuredMulti-round

Online Assessment

The initial online assessment usually includes three coding questions of varying difficulty, primarily focused on data structures and algorithms, resembling LeetCode-style problems. Candidates should prepare for a mix of easy to hard questions, as performance here is critical for advancing to the next rounds.

DSALeetCodeCoding Assessment

Technical Interviews

Technical interviews generally consist of two main components: data structures and algorithms (DSA) questions followed by system or database design discussions. Candidates should be ready to demonstrate problem-solving skills, articulate their thought processes, and design scalable systems based on given scenarios.

DSASystem DesignDatabase Design

Behavioral & HR Round

The final HR round focuses on cultural fit, communication skills, and background discussions, often feeling more conversational than technical. Candidates should be prepared to discuss their experiences, motivations, and how they align with the company’s values and team dynamics.

BehavioralCultural FitCommunication

Difficulty & Expectations

Overall, the interview process is perceived as challenging, especially in the technical rounds where candidates are expected to demonstrate a strong grasp of core concepts and problem-solving abilities. Candidates should approach each round with a mindset of continuous improvement and clarity in their explanations.

ChallengingExpectationsCore Concepts

What Candidates Wish They'd Done

Many candidates reflect on the importance of practicing system design and database-related questions, as these areas often carry significant weight in the evaluation process. Preparing for real-world applications of technical knowledge and articulating design decisions can be crucial for success.

PreparationSystem DesignDatabase Knowledge