How long does the Immobiliare.it interview process take?

Most candidates spend between 4 and 8 weeks from recruiter screen to offer. The onsite loop itself runs in a single day or is split across two half-days, with debrief and offer typically within 5 business days after.

How should I prepare specifically for Immobiliare.it?

Focus on three things: (1) the company DNA shown above - what they actually grade for, (2) the rounds in your loop, especially the round most candidates underestimate, and (3) drilling on the question types in this guide using a structured framework like CIRCLES or STAR.

Does this apply to engineering or design roles at Immobiliare.it?

The DNA stays the same - what changes is the round mix. SWE candidates face coding screens instead of Product Sense; designers face portfolio reviews and design exercises. The "what they value" and behavioral signals carry across all functions.

Other roles at Immobiliare.it:Product Manager Software Engineer Sales Marketing

Enterprise · Software Engineer Interview Guide

Interview language: English

How to Pass the Immobiliare.it Software Engineer Interview in 2026

The Immobiliare.it DNA (TL;DR)

Immobiliare.it's squad-based structure demands pragmatic thinking and a clear grasp of the Italian property market's nuances. Interviews test your ability to improve core products like property listings or the `Valutazione Immobiliare` tool with tangible, user-focused ideas.

The Immobiliare.it Interview Loop

Your onsite loop will typically consist of 5 rounds.

1
Round 1
Recruiter Screen
Motivation, role fit, logistics.
2
Round 2
Coding Screen
LeetCode-medium algorithmic problems under time pressure.
3
Round 3
System Design
Distributed systems, trade-offs at scale, architecture under constraints.
4
Round 4
Onsite Coding
LeetCode-hard, debugging, code clarity, edge cases.
5
Round 5
Behavioral / Leadership
Past evidence of ownership, influence, resolving conflict.

The Danger Zone: Top Reasons Candidates Fail

Based on our database of Immobiliare.it interview outcomes, avoid these common traps:

Not considering the fan-out problem for notifications to many users.
Failing to explain the impact of the decision on the project or team.
Not considering distributed rate limiting if the API is accessed across multiple servers.
Proposing a monolithic solution without considering microservices.

Test Yourself: Real Immobiliare.it Questions

Three real prompts pulled from our database.

Type · algorithmic

Given a list of property listings with their prices, find the N most expensive listings that are within a certain price range (e.g., between $X and $Y). Optimize for performance.

Type · coding

Write a function to parse a complex, nested JSON structure representing property features and extract all features that have a specific value (e.g., find all 'heating' features that are 'gas'). Ensure the code is clean, well-tested, and handles malformed JSON gracefully.

Type · past-experience

Tell me about a time you had a disagreement with a colleague or manager about a technical approach or decision. How did you handle it, and what was the outcome?

+ many more questions, signals, and worked examples

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Immobiliare.it Interview Question Bank

A sample from our database, grouped by round. Sign up to see the full set.

9 of 16 questions shown

Recruiter Screen

1
Type · motivation
What interests you about Immobiliare.it specifically, and how do you see your skills as a software engineer contributing to our mission of revolutionizing the real estate market?

Coding Screen

2
Type · algorithmic
Given a list of property listings with their prices, find the N most expensive listings that are within a certain price range (e.g., between $X and $Y). Optimize for performance.
3
Type · algorithmic
You are given a dataset of user search queries for properties. Design a function to suggest related search terms based on query similarity (e.g., 'apartments for rent' -> 'flats to let'). Consider efficiency for a large volume of queries.
+ 1 more questions in this round (sign up to unlock)

System Design

4
Type · design
Design a system to recommend properties to users based on their past viewing history, saved properties, and search queries. Consider scalability for millions of users and properties.
5
Type · design
Design a real-time notification system for new property listings that match a user's saved search criteria. How would you handle potentially millions of users and frequent listing updates?
+ 1 more questions in this round (sign up to unlock)

Onsite Coding

6
Type · coding
Write a function to parse a complex, nested JSON structure representing property features and extract all features that have a specific value (e.g., find all 'heating' features that are 'gas'). Ensure the code is clean, well-tested, and handles malformed JSON gracefully.
7
Type · debugging
A user reports that their saved search alerts are not being triggered for new properties. Debug the provided (buggy) code snippet that handles alert generation and identify the root cause.
+ 1 more questions in this round (sign up to unlock)

Behavioral / Leadership

8
Type · past-experience
Tell me about a time you had to make a significant technical trade-off on a project. What was the situation, what were the options, and what was the outcome?
9
Type · past-experience
Describe a situation where you encountered a major technical challenge or bug that was difficult to resolve. How did you approach it, and what did you learn from the experience?
+ 4 more questions in this round (sign up to unlock)