Optum Software Engineer candidates report a fundamentals-heavy process. It includes recruiter or HR screens, an online assessment in some accounts, project walkthroughs, basic coding and SQL, team-specific stack questions, and a closing HR or manager talk.
$118K
Avg. Base Comp
$143K
Avg. Total Comp
2-4 rounds
Typical Rounds
Not reported
Process Length
Candidate reports for Optum Software Engineer roles point to an interview that rewards knowing your own resume and the fundamentals more than grinding hard algorithms. Many candidates were asked to explain the architecture and their personal contribution behind a recent project, so be ready to defend every entry you list.
Coding questions are generally described as basic to mid-level. Reported examples include reversing a string, checking for a palindrome and a Python coding question. Candidates also mention data structures, DBMS and basic SQL, such as ordering the contents of a table. Fundamentals came up too, including data types in Java and JavaScript and the difference between an interface and abstraction. One candidate described an AI-based, CodeSignal-style assessment with three API-building tasks and a rate limiter.
Stack questions depend on the team. Reports mention Java, Spring Boot, microservices, Kafka, Hibernate and Elasticsearch on backend-leaning teams, Terraform scripts in an infrastructure discussion, and Angular modules on a frontend-leaning one. One candidate who applied for a .NET role learned at the end that the team mainly used Python and AI. Asking the recruiter about the actual stack early is worthwhile.
Round counts vary, from a two-round campus-style process to longer loops with several technical tests. Most finish with an HR or manager conversation built around situation-based and resume questions. Outcomes in these reports were mostly offers, with a few rejections.
Synthesized from 28 candidate reports by our editorial team.
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| Question | |
|---|---|
| Size of Joins | |
| String Mapping | |
| Sort Strings | |
| Hurdles In Data Projects | |
| Concurrent LLM Serving | |
| String Palindromes | |
| Impossibly Iterative Fibonacci | |
| Azure Kubernetes Infrastructure | |
| Your Strengths and Weaknesses | |
| Fast Food Database | |
| Prime to N | |
| Weighted Keys | |
| P-value to a Layman | |
| Liked Pages | |
| Bagging vs Boosting | |
| Daily Retention Summary | |
| Delivery Estimate Model | |
| Detecting ECG Tachycardia Runs | |
| The Brackets Problem | |
| Google Maps Improvement | |
| Most Repetition | |
| Valid Anagram | |
| Find Duplicate Numbers in a List | |
| Success Measurement | |
| Target Indices | |
| Priority Queue Using Linked List | |
| Customer Success vs. Free Trial | |
| Implementing the Fibonacci Sequence in Three Different Methods | |
| Prime Numbers Identification |
Synthesized from candidate reports. Individual experiences may vary.
Several candidates report an early recruiter or HR conversation before the technical rounds. One .NET candidate was contacted by a recruiter through Naukri. Expect questions about your background and resume. Prepare a clear introduction and a short answer on why you want to join Optum.
One candidate describes an AI-based, CodeSignal-style online round with four questions: three API-building tasks and a rate limiter, with unclear scoring. Another had a roughly 45-minute coding challenge as the first technical round. Others describe going straight into technical interviews.
Candidates describe technical conversations lasting roughly 45 minutes to an hour. They often open with a walkthrough of a recent project. They then move to basic-to-mid coding, SQL, data structures or DBMS questions, and stack topics such as Java, Spring Boot, microservices, Kafka, Elasticsearch, .NET or Terraform. One candidate shared their screen and solved problems independently, asking clarifying questions as needed.
Some candidates report a second technical round. One had two screen-share technical tests that covered problem-solving and then domain knowledge such as Kafka and DBMS. A senior candidate faced a separate round on listed technologies like Elasticsearch. Others describe only a single technical conversation, so depth varies by team and interviewer.
Many candidates describe closing with an HR or manager discussion. Reported topics include situation-based and resume-based questions and a general conversation about background and past work. One candidate described a package discussion with HR after the technical rounds. Have concrete examples from past work ready.
