INFINIDAT Software Engineer Interview: Questions & Prep (2026)

INFINIDAT builds enterprise-grade storage systems, primarily the InfiniBox (primary storage) and InfiniGuard (data protection) product lines, used by large banks, healthcare providers, and telcos worldwide. As of July 2026, knok's job radar shows 45 open Software Engineer roles at INFINIDAT, reflecting active hiring across their engineering teams.

The interview process candidates report typically runs 3-5 rounds over 2-4 weeks: a recruiter or HR screening call, one or two technical rounds covering data structures, algorithms, and system design, and a final round that includes behavioural or culture-fit questions. Some candidates also report an initial online coding test before the live interviews.

The technical focus at INFINIDAT leans heavily toward distributed systems, storage internals, reliability engineering, and low-latency design. If you have worked on file systems, block storage, replication, or high-availability infrastructure, bring that experience front and centre in your answers.

These are the question areas candidates typically report seeing across INFINIDAT Software Engineer interviews, based on community feedback and role requirements.

1. How would you design a distributed storage system that guarantees data durability even under node failures?
2. Explain how you handle race conditions in a multi-threaded or multi-process environment. Give a concrete example.
3. Walk us through how you would debug a latency spike in a production storage service.
4. What is the difference between synchronous and asynchronous replication, and when would you choose each?
5. How would you implement a cache eviction policy? What are the trade-offs between LRU, LFU, and ARC?
6. Describe a time you optimised a slow or resource-heavy piece of code. What was your process?
7. How do you ensure backward compatibility when making a breaking change to an internal or external API?
8. Tell me about a time you disagreed with a technical decision on your team. How did you approach it?
9. How would you design a test strategy for a distributed system where failures are non-deterministic?
10. What is your experience with file system internals, block storage, or object storage?
11. Describe a situation where you had to make a critical architectural decision under time pressure. What did you decide and why?
12. How do you stay current with developments in storage or infrastructure technology?

Each answer below follows the STAR structure: *Situation, Task, Action, Result*. Adapt these to your own experience.

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Q: Walk me through how you debugged a latency spike in a production system.

*Situation:* At my previous company, our microservice handling storage metadata requests started returning slow responses during peak business hours. Users were complaining and escalations were coming in.

*Task:* I had to identify the root cause quickly, without taking the service offline or causing a broader outage.

*Action:* I added structured logging to capture per-request timing at each layer. I used distributed tracing to isolate which downstream call was slow and found that one database query was doing a full table scan on a table that had grown considerably over the past quarter. I created an index using an online migration (no lock, no downtime) and deployed it during a low-traffic window.

*Result:* Response times returned to normal within minutes of the index being applied. I wrote up the process as a runbook and the team adopted structured tracing as a standard practice going forward.

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Q: Describe a time you optimised slow or resource-heavy code.

*Situation:* A batch job at my team processed storage snapshot metadata and was taking several hours to complete, pushing past our allowed maintenance window.

*Task:* I was asked to bring the run time down so the job could finish within the window without needing emergency extensions.

*Action:* I profiled the job and found it was making individual database reads inside a loop, each pulling the same reference data repeatedly. I replaced those with a single bulk fetch at the start, stored the results in a local map, and added parallelism for snapshot batches that had no dependencies on each other.

*Result:* The job completed in a fraction of its original run time and has not missed its window since. The team reused the same pattern for two other batch jobs with similar problems.

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Q: Tell me about a time you disagreed with a technical decision. How did you handle it?

*Situation:* My team decided to use a single large message queue to handle all storage events across all tiers, in order to keep the architecture simple.

*Task:* I believed this would become a bottleneck at peak loads and that mixing high-priority and low-priority events on one queue would cause priority inversion.

*Action:* Rather than raising the concern verbally only, I put together a short written proposal with a performance model showing projected queue depth under our peak load estimates. I suggested a partitioned approach with separate lanes per storage tier and priority level, and asked for a short spike to validate the model.

*Result:* The team agreed to a hybrid design, keeping one queue for low-volume admin events but partitioning the high-volume data paths. Queue contention during peak windows dropped noticeably, confirmed in our load tests.

For behavioural questions use the STAR structure: *Situation* (brief context), *Task* (what you were responsible for), *Action* (what you specifically did, step by step), *Result* (measurable or observable outcome). Keep Situation and Task short. Spend most of your time on Action and Result.

For system design questions follow this sequence:

1. Clarify requirements before drawing anything. Ask about scale, consistency needs, durability guarantees, and read-vs-write ratios.
2. Sketch the high-level architecture and name the main components.
3. Deep-dive on the parts the interviewer probes (often consistency, replication, or failure handling at INFINIDAT).
4. Discuss trade-offs explicitly. Do not present one solution as if it is obviously correct.
5. Mention how you would monitor and alert on this system in production.

For coding questions think aloud from the start. State your assumptions, pick the simplest correct solution first, then optimise if asked. State the time and space complexity of your approach before you finish writing.

Deep systems thinking. INFINIDAT's products sit at the core of enterprise infrastructure, so interviewers pay close attention to whether you reason about durability, consistency, and failure modes naturally, not just as an afterthought.

Debugging rigour. Candidates who walk through a systematic debugging process (instrument, isolate, hypothesise, verify) stand out. Vague answers like 'I would check the logs' without describing what you look for will not score well.

Clear communication under pressure. Storage systems are complex, and interviewers want to see that you can explain trade-offs to teammates who may not share your exact background. Practise explaining your reasoning out loud, not just writing code silently.

Ownership and follow-through. Behavioural questions at INFINIDAT tend to probe whether you see problems through to completion. Answers that end with 'I raised the issue and handed it off' are weaker than ones that end with a clear outcome you personally helped deliver.

Honesty about gaps. Enterprise storage is a specialised domain. If you have not worked directly with file systems or block storage, say so and then connect your distributed systems or reliability experience to the problems INFINIDAT solves.

Week 1: Core coding and algorithms. Practise data structures (trees, graphs, heaps, hash maps) and common algorithm patterns (sliding window, two pointers, dynamic programming basics). Focus on problems tagged with 'concurrency' and 'system design' on coding practice platforms.

Week 2: Systems design for storage. Study replication (synchronous vs asynchronous), consistency models (strong, eventual, causal), consensus algorithms (Raft and Paxos at a high level), and storage internals (how SSDs, RAID, and write-ahead logs work). INFINIDAT's public product documentation is useful background reading for context on what their systems actually do.

Week 3: Behavioural preparation and mock interviews. Write down several stories from your own experience covering optimisation, debugging, disagreement, and ownership. Practise telling each one in under 2 minutes using the STAR structure. Do at least one timed mock interview with a peer or on a platform that gives structured feedback.

Before every round: Re-read the job description and map your strongest experience to the listed requirements. Prepare 2-3 questions to ask the interviewer about the team's current engineering challenges.

Skipping the clarification step in system design. Jumping straight to a solution before understanding scale and constraints is the most common reason candidates lose marks on design rounds. Always ask first.

Giving shallow behavioural answers. 'We worked as a team and solved the problem' is not a STAR answer. Interviewers want to know what you specifically did. Use 'I', not 'we', when describing your own actions.

Ignoring reliability and failure modes. In a design question, if you do not mention what happens when a node goes down, a disk fails, or a network partitions, INFINIDAT interviewers will probe it directly. Build failure handling into your design from the start.

Talking through code without tracing an example. When solving a coding problem, walk through a small input by hand before declaring your solution correct. Many bugs surface this way that would otherwise cost you the round.

Not asking questions at the end. Candidates who ask nothing signal low interest. Prepare thoughtful questions about the team's current reliability challenges, their tech stack, or how they handle on-call responsibilities.