Eli Lilly software engineer interviews lean heavily on behavioral, resume-driven conversations, with technical depth that ranges from none to LeetCode-style coding depending on the specific role and team.
$118K
Avg. Base Comp
$140K
Avg. Total Comp
Not reported
Typical Rounds
Not reported
Process Length
Eli Lilly's software engineer interviews, based on the candidate accounts here, spend a lot of time on resume and project deep-dives rather than pure algorithmic testing. Candidates describe being asked to walk through specific projects in detail and explain what they built and the technical choices behind it, often inside a STAR-style behavioral framework. One internship candidate was told upfront that STAR-format answers were expected.
The technical bar varies by role. One software engineer candidate faced five coding questions in one round and six in another, all general LeetCode-style easy-to-medium problems. An internship candidate got an egg-drop style DSA problem. Another candidate was asked about OOP concepts, collections, and a framework. One engineering candidate reported SQL, Python, and C basics plus some machine learning concepts. Others described rounds that were mostly conversation about background, motivation, and why Eli Lilly specifically.
Process length is similarly inconsistent. One internship candidate heard back within about a week. One engineering candidate described a process that stretched over several months, with behavioral rounds involving different functional leaders and the hiring manager. One candidate was pressed during interviews about data engineering, accepted a Software Engineer offer, and then received a contract for a Data Engineer role. It's worth confirming the exact role in writing as you go.
Given this mix, the most useful preparation is to have clear STAR stories ready about your projects, teamwork, mistakes, and conflicts, along with a specific answer for why Eli Lilly. Pair that with a review of basic DSA topics like binary search, OOP fundamentals, and SQL in case your loop turns out to be more technical.
Synthesized from 13 candidate reports by our editorial team.
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Real interview reports from people who went through the Eli Lilly And Company process.
What stood out to me most was how much of the process was conversational rather than intensely technical. I first heard back about a month after applying online, and the hiring manager set up a short 20-minute call where I had to walk through a problem I had solved in a previous role using a PPT. That round felt more like explaining my thinking and impact than being grilled on code, especially since the job description had already been removed from the website by then, which made the whole thing feel a little less straightforward.
After that, the process moved on to campus recruiting. I spoke with two recruiters about my background, why I wanted to work at Eli Lilly, and what I hoped to do there. The on-site portion was two separate one-on-one interviews, about an hour each, with two employees. Those were mostly behavioral and company-focused, with a lot of questions about my experience and fit. I also remember being asked about a conflict with a coworker, and there were several questions about the company itself. One interviewer also pushed into technical territory and asked about OOP concepts, collections, and a framework, but it still felt pretty light compared with a traditional software engineering loop.
The overall vibe was friendly and smooth, and I even got to interact with employees at lunch, which made the process feel welcoming. At the same time, I felt like they asked a lot of questions overall, so it helped to be ready to talk clearly about past projects and why Eli Lilly specifically. I ended up declining the offer, but the experience itself was positive and not especially stressful.
Prep tip from this candidate
Be ready to present a past project clearly in a short slide-based explanation, and practice answering company-fit questions like why Eli Lilly and what you want to do there. It also helps to review basic OOP, collections, and a framework you’ve used, since those came up alongside 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 Eli Lilly And Company
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| Question | |
|---|---|
| Justify a Neural Network | |
| Client Solution Pushback | |
| Loan Model | |
| String Palindromes | |
| Your Strengths and Weaknesses | |
| 2nd Highest Salary | |
| Monthly Customer Report | |
| Last Transaction | |
| Weighted Keys | |
| Total Spent on Products | |
| Hurdles In Data Projects | |
| Cumulative Distribution | |
| Retailer Data Warehouse | |
| P-value to a Layman | |
| Detecting ECG Tachycardia Runs | |
| Cumulative Reset | |
| Always Excited Users | |
| Subscription Retention | |
| Ranking Metrics | |
| Brain Cancer Treatment Outcomes | |
| Sum to Zero | |
| Flatten JSON | |
| Valid Anagram | |
| Spanish Scrabble | |
| 85% vs 82% | |
| Rider Discount | |
| Digit Accumulator | |
| Multi-Reaction | |
| Time Difference |
Synthesized from candidate reports. Individual experiences may vary.
Several candidates describe an initial call with a recruiter or hiring manager covering background and experience. One hiring manager call ran about 20 minutes and asked the candidate to walk through a past problem using a short presentation. Campus recruiters in another process asked why the candidate wanted to work at Eli Lilly. This stage is typically conversational rather than technical.
Across most experiences, interviewers ask candidates to walk through specific resume projects: what was built, which technical choices were made, and what the candidate contributed. This shows up in both internship and full-time software engineer accounts, and candidates report it as a major focus of the loop.
Most candidates encounter STAR-style behavioral questions. Examples include describing a mistake and how it was handled, a conflict with a coworker, working with a team, improving a project's performance, or what they did to impress other employees. Some interviewers state upfront that they want structured STAR answers.
Technical depth varies sharply by role and team. Some candidates report a technical assessment, rounds with multiple LeetCode-style easy-to-medium coding questions, a DSA puzzle such as the egg-drop problem, OOP and collections questions, or SQL, Python, and C basics. Other candidates, including one internship candidate, report no coding at all, just conversation about their resume and interests.
Some candidates went through several interviews in one visit. One had back-to-back technical, leadership, and HR conversations of roughly 20 to 30 minutes each. Another had two one-hour one-on-ones with employees. Interviewers were generally described as friendly and professional, and one candidate also met employees over lunch.
Reported timelines vary widely. One internship candidate heard back within about a week, while one full-time engineering candidate went through a process lasting several months with multiple behavioral rounds. One candidate accepted a Software Engineer offer and then received a contract for a Data Engineer role, so confirming role details in writing is a reasonable precaution.
