John Deere Software Engineer interviews typically combine a recruiter/HR screen, a HackerRank coding assessment, one or more technical or live-pairing rounds, and multiple STAR-format behavioral interviews, with the exact mix shifting by team.
$116K
Avg. Base Comp
$135K
Avg. Total Comp
Not reported
Typical Rounds
Not reported
Process Length
John Deere's software engineer interviews typically begin with a recruiter or HR phone screen, then move into one or two technical checkpoints before wrapping up with STAR-format behavioral rounds. Across the experiences gathered, HackerRank is the most common vehicle for the coding assessment, usually covering easy-to-medium problems. One candidate saw two multiple-choice items, an easy SQL query, and a straightforward LeetCode-style problem. Another chose Java and handled a SQL query, a coding problem, and building a REST API GET endpoint. Several candidates report live coding or pairing sessions with actual team members rather than isolated algorithm drills, where communicating your thinking mattered as much as reaching an answer. One live session involved completing React components with form state, validation, and submission logic, and one candidate was asked to architect an e-commerce data flow as a system design exercise.
Behavioral interviews carry real weight at John Deere. Multiple candidates describe several STAR-format rounds, in one case with the same five questions repeated across different interviewers. Topics included diversity and inclusion, accountability, innovation, communication, leadership, and going above and beyond for a customer. The technical mix shifts by team and stack. An embedded systems candidate was asked about arrays, pointers, and microcontroller architecture. Another heard repeated questions on .NET, SQL Server, and DBMS concepts. A third recalled fundamentals like linked lists, C/C++ pointers, and unions versus structs. Outcomes across the collected reports are mixed, so treat any single candidate's path as one data point rather than a universal script.
Synthesized from 15 candidate reports by our editorial team.
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Real interview reports from people who went through the John Deere process.
The interview started with a phone screening with the recruiter, just a standard conversation about background and fit. Then came the technical round—45 minutes on HackerRank with two problems at the easy-to-medium level. Not a grind-fest, just a solid test of how you code and think through problems.
After that were two behavioral interviews using the STAR method. One question was about a time I went above and beyond for a customer. The other was about stepping into a leadership role. The interviewers were thoughtful and genuinely engaged, which made the whole thing feel less like an interrogation and more like a real conversation.
Technically, John Deere covers the fundamentals: linked lists, pointers in C/C++, unions versus structs, logic puzzles like detecting shapes in 2D arrays, data structures, sorting, searching, complexity analysis. Some roles also include computer vision and image processing topics. The overarching theme is clear—know your fundamentals and think algorithmically.
What really stood out was the culture. Good colleagues, flexible schedule, meaningful work, genuine growth opportunities. The compensation was fair. The company actually seemed to care about how candidates felt through the process. I got the offer and accepted it.
Prep tip from this candidate
The technical screening tests fundamentals—linked lists, pointers, C/C++ data structures—with easy-to-medium problems and logic puzzles like detecting shapes in 2D arrays. Prep STAR format stories about customer advocacy and leadership for the behavioral rounds.
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Sourced from candidate reports and verified by our team.
Topics based on recent interview experiences.
Featured question at John Deere
Find the longest increasing subsequence in a list of integers.
| Question | |
|---|---|
| Hurdles In Data Projects | |
| Alternative Vendor Tradeoff | |
| Processing Large CSV | |
| 2nd Highest Salary | |
| Merge Sorted Lists | |
| Prime to N | |
| Bagging vs Boosting | |
| Size of Joins | |
| The Brackets Problem | |
| Real-Time Transaction Streaming | |
| Level Of Rain Water In 2D Terrain | |
| Cyclic Detection | |
| Term Frequency | |
| Find Duplicate Numbers in a List | |
| Multi-Reaction | |
| RAG Strict Source Control | |
| Merge N Sorted Lists | |
| Worker Distribution Dilemma | |
| Offer Matching API Design | |
| Loan Model | |
| Seller Type Modeling | |
| Solo ML Deployment | |
| String Palindromes | |
| The Pirate’s Hunt | |
| Data Stream Median | |
| Gas Station Counting | |
| Shortest Transformation | |
| Hidden Substring Segment | |
| International e-Commerce Warehouse |
Synthesized from candidate reports. Individual experiences may vary.
Most candidates report an initial phone screen with a recruiter or HR representative covering background, availability, salary expectations, and basic fit for the role. This stage is typically conversational rather than technical, though one report mentions it being handled by a third-party HR contact before the hiring team got involved.
Several candidates describe a HackerRank assessment with two to four questions spanning multiple-choice items, SQL queries, and coding problems at an easy-to-medium difficulty. One candidate chose Java and was asked to write a SQL query, solve a coding problem, and build a REST API GET endpoint.
Technical rounds commonly involve live coding or pairing with team members, with interviewers evaluating communication and problem-solving as much as correctness. Depending on the team, this may include data structures and algorithms fundamentals, C/C++ pointers or embedded concepts, React component building, .NET and SQL Server topics, or a system design discussion such as architecting an e-commerce flow.
Nearly every candidate describes one or more behavioral rounds using the STAR method. Questions covered diversity and inclusion, accountability, innovation, communication, leadership, and going above and beyond for a customer. One candidate reported the same set of questions being asked again by different interviewers, which they read as a check for consistency.
