HubSpot Software Engineer candidates commonly report an API-focused assessment, behavioral screening, live coding, and system design, with recent reports also describing HTTP/JSON and project-depth discussions.
$160K
Avg. Base Comp
$215K
Avg. Total Comp
4-6 rounds
Typical Rounds
3-5 weeks
Process Length
HubSpot Software Engineer interviews often begin with a practical assessment rather than a purely algorithmic screen. Several candidates describe a time-boxed API task: retrieve data from an endpoint, transform it according to specified rules, and submit the result. Correctness at the interface and edge cases matter—one account notes that the API returned a successful response only when the output was exactly right, leaving limited time for tests.
Later stages vary by team and date, but behavioral conversations recur alongside coding and design. Candidates report questions about teamwork, feedback, company motivation, previous projects, and handling mistakes. Prepare concise examples that identify your role, decisions, and outcome. Live coding has included merging and sorting arrays, hashmap-style problems, JavaScript fundamentals, and medium-to-hard LeetCode-style work. Explain your reasoning, tests, and edge cases as you proceed.
System design also appears frequently, with supplied examples including Calendly, Netflix features, and a general system-scaling discussion. Be ready to clarify requirements, identify bottlenecks, and discuss components, storage, caching, load balancing, reliability, and other relevant trade-offs. One candidate was told that an updated onsite contained one coding interview, two system-design interviews, and one behavioral interview, but had not yet completed that loop. Treat the exact sequence as team- and date-dependent, and confirm the current format with recruiting.
Synthesized from 23 candidate reports by our editorial team.
Had an interview recently?
Share your experience. Unlock the full guide.
Real interview reports from people who went through the Hubspot process.
Share your own interview experience to unlock all reports, or subscribe for full access.
Sourced from candidate reports and verified by our team.
Topics based on recent interview experiences.
Featured question at Hubspot
Given two sorted lists, write a function to merge them into one sorted list.
| Question | |
|---|---|
| Address Schema | |
| Target Indices | |
| Employee Benefits Outreach | |
| String Palindromes | |
| Scalable Data Pipelines | |
| Client Solution Pushback | |
| Why Do You Want to Work With Us | |
| Marketing Workflow Optimization | |
| Weighted Average Sales | |
| Reddit-like Notifications | |
| Dropbox Database | |
| Meta in an Emerging Market | |
| 2nd Highest Salary | |
| Top Three Salaries | |
| Empty Neighborhoods | |
| Closest SAT Scores | |
| Subscription Overlap | |
| Monthly Customer Report | |
| Rolling Bank Transactions | |
| Top 3 Users | |
| Random SQL Sample | |
| Prime to N | |
| Comments Histogram | |
| Upsell Transactions | |
| Find the Missing Number | |
| Raining in Seattle | |
| String Shift | |
| Customer Orders | |
| Bagging vs Boosting |
Synthesized from candidate reports. Individual experiences may vary.
Candidates often report a roughly three-hour assessment involving GET/POST requests, JSON transformation, grouping data, or other API handling. More recent reports also describe a timed, progressive coding exercise. Treat response validation and boundary cases as part of the problem, not as setup details.
Candidates report recruiter or behavioral conversations covering why HubSpot, prior projects, feedback, teamwork, and work situations. Prepare specific stories with your role, decisions, and outcome; some processes use this conversation before the technical loop.
Reported coding prompts range from merge-style arrays or lists and hashmap-style problems to JavaScript concepts and HTTP/JSON-based problem solving. Candidates describe an emphasis on explaining reasoning, test cases, correctness, and edge cases rather than only reaching a solution.
Candidates report system design prompts such as video streaming, Dropbox-like storage, scalable systems, or feature architecture. Discuss requirements, APIs, data choices, and trade-offs; some later loops also include a detailed conversation about a recent project.
