Visa Software Engineer candidates report online coding assessments followed by technical, project-focused, and behavioral or hiring-manager conversations. Prepare for timed DSA work and clear explanations of your engineering decisions.
$169K
Avg. Base Comp
$230K
Avg. Total Comp
3-6 rounds
Typical Rounds
2 months
Process Length
Visa Software Engineer interviews commonly begin with an online coding assessment, then move into technical and conversational stages. Candidate accounts vary by team and level, but several describe timed CodeSignal or HackerRank-style assessments with easy-to-medium data-structures-and-algorithms questions; some encountered harder questions or a broader mix under time pressure. Practice producing correct, readable solutions while explaining your approach, particularly for arrays, strings, linked lists, graphs, and sliding-window-style problems.
Project depth matters alongside coding. Candidates report technical discussions that start from the resume and drill into an API call, project decisions, data handling, or the technologies named in a project. Be able to explain what you built, why you made key technical choices, and which tradeoffs you would revisit. Keep those answers grounded in your own work rather than adding tools you cannot defend.
Later conversations may combine behavioral questions with software fundamentals. Reports include OOP, testing, REST, operating systems, networking, SQL/DBMS, and high-level system design. Prepare concise examples about collaboration, feedback, difficult work challenges, and why the role interests you. For design prompts, articulate requirements, major components, scaling considerations, and tradeoffs before diving into implementation. Exact sequencing differs across accounts, but the recurring preparation theme is moving comfortably between coding, engineering fundamentals, and your own project decisions.
Synthesized from 33 candidate reports by our editorial team.
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Real interview reports from people who went through the Visa process.
The interview process consisted of five rounds, ending with an offer. It included a HackerRank online assessment followed by two technical interviews, and I was nervous going in. Staying confident and keeping my problem-solving skills sharp made a real difference.
Questions asked: The HackerRank assessment included Python and SQL questions. On the Python side, one question asked me to process an array of transaction IDs and return the first duplicate transaction as efficiently as possible — I solved it using a hash map (dictionary) in O(n) time. Another question involved calculating the running sum of values in an array. The SQL section covered joins, GROUP BY, aggregate functions, and filtering. One task required finding the top five customers by number of transactions; another involved joining customer and transaction tables to calculate total spending per customer.
During the technical interview, the interviewer asked me to explain my approach before coding, discuss time and space complexity, and describe how I would handle edge cases such as empty arrays, duplicate values, and null records. There were also follow-up questions about why I chose a dictionary instead of nested loops and how the solution would scale for large datasets.
Overall, the interview focused more on problem-solving, writing clean code, and explaining my reasoning than on memorizing language-specific syntax.
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Sourced from candidate reports and verified by our team.
Topics based on recent interview experiences.
Featured question at Visa
Write a query to select the top 3 departments with at least ten employees and rank them according to the percentage of their employees making over 100K in salary.
| Question | |
|---|---|
| Closest SAT Scores | |
| Top Three Salaries | |
| Rolling Bank Transactions | |
| Total Spent on Products | |
| Sum to N | |
| Bagging vs Boosting | |
| Size of Joins | |
| Alphabet Sum | |
| Employees Before Managers | |
| Resumable Fact Table Load | |
| Hurdles In Data Projects | |
| Fewer Orders | |
| Count Transactions | |
| RAG Strict Source Control | |
| Filling Supermarket Bag | |
| Implementing the Fibonacci Sequence in Three Different Methods | |
| Modifying a Billion Rows | |
| Swap Variables | |
| Slow SQL Query | |
| Concurrent LLM Serving | |
| Production Model Monitoring | |
| Mouse Search | |
| User Event Data Pipeline | |
| Check Matching Parentheses | |
| The Longest Journey | |
| Search Timeout | |
| Three Indexes Adding Zero | |
| Solo ML Deployment | |
| SageMaker Deployment Architecture |
Synthesized from candidate reports. Individual experiences may vary.
Candidates report an initial CodeSignal or HackerRank-style assessment in several Visa Software Engineer processes. Formats differed: some described three or four questions, and reported difficulty ranged from easy-to-medium to more demanding array or sorting problems. Timed practice can help you prioritize correctness and explainable solutions.
Candidates report one or more technical conversations that may include live LeetCode-style coding as well as questions on areas such as OOP, REST, testing, OS, networking, SQL, DBMS, Java, or backend fundamentals. The exact topic mix appears to vary by team, so connect core concepts to practical engineering decisions.
Several candidates describe project walkthroughs and follow-up questions about APIs, data quality, databases, caches, authentication, or technologies listed on the resume. Some also report a conversational system-design prompt, where outlining components, functions, scaling, and tradeoffs may be more important than producing a detailed diagram.
Candidates report behavioral or hiring-manager discussions about their background, interest in Visa, teamwork, feedback, difficult challenges, and preferred team. These conversations may also include technical or resume follow-ups, so prepare concrete examples while keeping your project narrative technically precise.
