At Optumrx, a Software Engineer plays a pivotal role in designing, building, and maintaining the digital infrastructure that powers pharmacy care services for millions of members. As a key division of UnitedHealth Group, Optumrx processes vast volumes of prescription transactions, manages complex clinical data, and delivers user-facing digital health experiences. Your work directly impacts patients' ability to access life-saving medications efficiently, securely, and affordably. The engineering organization at Optumrx tackles challenges of massive scale, high availability, and strict regulatory compliance. Whether you are developing modular frontend interfaces using modern JavaScript frameworks or architecting high-throughput backend services, your code must be resilient and performant. You will work on collaborative product teams that bridge the gap between complex healthcare workflows and seamless digital solutions. This role is highly collaborative and technically rewarding. You will have the opportunity to work with cutting-edge cloud technologies, modern web development practices, and robust databases. For engineers who thrive on solving real-world problems that have a direct, positive impact on human health and well-being, offers an inspiring and mission-driven engineering environment. Optumrx
Initial Hiring Manager Screen
reportedFirst interaction with the hiring manager to assess initial fit and discuss the role.
What to demonstrate
- First interaction with the hiring manager to assess initial fit and discuss the role
- Depth in React
How to prepare
- Prepare two projects you led end to end, each with the decision you owned and what it cost.
- Have three questions about the team's roadmap and how success is measured in the first six months.
Deep-Dive Technical Evaluations
reportedIn-depth technical assessments tailored to the specific technologies and frameworks listed in the job posting.
What to demonstrate
- In-depth technical assessments tailored to the specific technologies and frameworks listed in the job posting
- Depth in React
How to prepare
- Answer aloud and timed: How do you handle event bubbling and capture in modern JavaScript?
- Answer aloud and timed: Describe how you would optimize a React application that is experiencing rendering performance issues.
Hybrid Technical-Managerial Discussion
reportedFinal discussion that evaluates both technical skills and collaborative working style.
What to demonstrate
- Final discussion that evaluates both technical skills and collaborative working style
- Depth in React
How to prepare
- Answer aloud and timed: Explain how you manage state across a complex, multi-layered component tree.
- Answer aloud and timed: What are the core pillars of Object-Oriented Programming (OOP), and how have you applied them in your recent projects?
PracHub editorial advice for the preparation topics above.
Think out loud
Your interviewers want to understand your problem-solving process. Continually explain your thoughts, assumptions, and choices while you write code.
Focus on the basics
Ensure your foundational knowledge of OOP, SQL, and your primary programming language is rock-solid. A strong grasp of the basics is highly valued over niche framework expertise.
Understand the healthcare context
Take some time to learn about Optumrx's business model. Showing that you appreciate the scale, security, and compliance needs of pharmacy benefit management will set you apart.
Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.
Build a functional React component (such as a search filter or interactive list) from scratch.
Build a functional React component (such as a search filter or interactive list) from scratch.
Approach
- Restate the input: its shape, its size, and what is guaranteed about it.
- Name the brute-force solution and its complexity before improving on it.
- Choose the data structure from the access pattern, not from familiarity.
- State the target complexity and say which constraint rules the naive version out.
Follow-up
- How does this change if the input no longer fits in memory?
- What is the worst case, and how likely is it on real data?
Archive a resource graph without breaking live references or recursing
Resources reference other resources within a tenant; for the largest tenant the reference table holds up to 2,000,000 nodes and 8,000,000 edges. Archiving a resource must archive everything reachable from it that nothing outside the set still references, refuse when a live external referrer exists, and terminate when references form cycles, which they legitimately do. Produce the archive order and the refusal list, targeting O(V+E). Say what stops the traversal crossing a tenant boundary, and why recursion is the wrong control structure at this size.
Approach
- Load the subgraph with the tenant predicate on both endpoints of the edge, not only on the side you started from. Scoping the left table alone is the classic cross-tenant leak: one mis-entered edge then pulls another tenant's resources into the traversal and, worse, into the archive.
- Traverse iteratively with an explicit stack. A 2,000,000-node graph can hold a chain deep enough to exhaust a native stack in the low tens of thousands of frames, and that failure is a process crash rather than an error you can return.
- Treat cycles as data rather than corruption: compute strongly connected components with Tarjan in O(V+E) using its own explicit stack, then condense. The condensation is a DAG, so a topological order over it gives the archive order, and every member of a component archives in one transaction because no order within a cycle is valid.
- Decide refusals with reverse edges. A candidate is archivable only if every in-edge originates inside the candidate set, so build the transpose or count in-degrees restricted to the visited set, and emit each blocked resource with the id of the external referrer, which is the only part of the answer an operator can act on.
Follow-up
- The graph is read in one query and the archive writes a minute later. What can change in between, and how do you make the write safe?
- The candidate set is 400,000 resources. Is that one transaction, and if not, what does a half-finished archive look like to a reader?
Identify the heaviest tenants in a five-minute window under memory pressure
The edge service handles about 3,000 requests per second across roughly 50,000 tenants, peaking near 9,000. Expose the 50 heaviest tenants by request count over the trailing five minutes so limits can be tightened before one tenant's backfill starves the fleet. You may not retain five minutes of raw records. Give the exact solution and its memory, then the bounded-memory approximation with its error stated as a formula, and say which you would ship and at what tenant cardinality that choice changes.
Approach
- Do the exact version first, because it is affordable at this cardinality: a ring of 300 one-second counters per tenant, advanced lazily, is 1,200 bytes of counters per tenant and roughly 60 to 90 MB for 50,000 tenants with overhead. Carry a running total and subtract the bucket you overwrite so a window read is O(1) rather than 300 adds.
- Extract the top 50 with a size-k min-heap over the tenant sums: O(d log k) for d tenants, against O(d log d) to sort them all. Maintaining the heap continuously instead of on query requires a tenant-to-heap-index map, because incrementing a count already inside the heap means sifting from a known position, and without that map you rebuild the heap on every request.
- State the approximation precisely rather than gesturing at sketches. Misra-Gries with m counters retains every item whose true count exceeds N/(m+1), and each retained count underestimates the truth by at most N/(m+1). With m = 1,000 and N = 900,000 requests in the window the error is roughly 900 requests, which is fine for spotting a tenant sending 50,000 and useless for ranking two tenants 200 apart.
- Say what breaks when the window slides: Misra-Gries and Space-Saving are insert-only and cannot be decremented as records age out. The workable construction is one summary per sub-window, say ten seconds, with 30 summaries merged at query time, and the merged error is the sum of the per-summary errors, so the bound degrades linearly in the number of sub-windows.
Follow-up
- The heaviest tenant is heavy because of one export job rather than user traffic. Should the limiter treat those as the same tenant?
- Two tenants sit tied at the boundary of the top 50. Does your answer flap, and does the flapping matter?
Write a SQL query to retrieve data across multiple tables using complex joins and aggregations.
Write a SQL query to retrieve data across multiple tables using complex joins and aggregations.
Approach
- Name the grain you start from and join outward from it.
- Check whether any join is one-to-many before aggregating, or the sums inflate.
- Say which index the query would use, and what makes it unusable.
- Handle the rows that do not match: that is usually the actual question.
Follow-up
- How does the query change if that join becomes one-to-many?
- What happens to this when the table is ten times larger?
What is database normalization, and when might you intentionally denormalize a database schema?
What is database normalization, and when might you intentionally denormalize a database schema?
Approach
- Name the grain you start from and join outward from it.
- Check whether any join is one-to-many before aggregating, or the sums inflate.
- Say which index the query would use, and what makes it unusable.
- Handle the rows that do not match: that is usually the actual question.
Follow-up
- How does the query change if that join becomes one-to-many?
- What happens to this when the table is ten times larger?
How do you optimize a slow-running database query in a high-transaction system?
How do you optimize a slow-running database query in a high-transaction system?
Approach
- Name the grain you start from and join outward from it.
- Check whether any join is one-to-many before aggregating, or the sums inflate.
- Say which index the query would use, and what makes it unusable.
- Handle the rows that do not match: that is usually the actual question.
Follow-up
- How does the query change if that join becomes one-to-many?
- What happens to this when the table is ten times larger?
Explain the difference between various React hooks (e.g., `useState`, `useEffect`, `useMemo`) and when to use
Explain the difference between various React hooks (e.g., useState, useEffect, useMemo) and when to use them.
Approach
- Clarify what is being asked and what a complete answer contains.
- State your assumptions explicitly before working the problem.
- Say what you would check first and why it is the highest-information step.
- Work from the requirement backwards to the design.
Follow-up
- What assumption would you test first?
- How would you know your answer was wrong?
Describe how you would optimize a React application that is experiencing rendering performance issues.
Describe how you would optimize a React application that is experiencing rendering performance issues.
Approach
- Clarify what is being asked and what a complete answer contains.
- State your assumptions explicitly before working the problem.
- Say what you would check first and why it is the highest-information step.
- Work from the requirement backwards to the design.
Follow-up
- What assumption would you test first?
- How would you know your answer was wrong?
Explain how you manage state across a complex, multi-layered component tree.
Explain how you manage state across a complex, multi-layered component tree.
Approach
- Clarify what is being asked and what a complete answer contains.
- State your assumptions explicitly before working the problem.
- Say what you would check first and why it is the highest-information step.
- Work from the requirement backwards to the design.
Follow-up
- What assumption would you test first?
- How would you know your answer was wrong?
What are the core pillars of Object-Oriented Programming (OOP), and how have you applied them in your recent p
What are the core pillars of Object-Oriented Programming (OOP), and how have you applied them in your recent projects?
Approach
- Clarify what is being asked and what a complete answer contains.
- State your assumptions explicitly before working the problem.
- Say what you would check first and why it is the highest-information step.
- Work from the requirement backwards to the design.
Follow-up
- What assumption would you test first?
- How would you know your answer was wrong?
Explain the concept of dependency injection and why it is beneficial in enterprise applications.
Explain the concept of dependency injection and why it is beneficial in enterprise applications.
Approach
- Clarify what is being asked and what a complete answer contains.
- State your assumptions explicitly before working the problem.
- Say what you would check first and why it is the highest-information step.
- Work from the requirement backwards to the design.
Follow-up
- What assumption would you test first?
- How would you know your answer was wrong?
How do you design a class structure that is easily extensible but closed for modification?
How do you design a class structure that is easily extensible but closed for modification?
Approach
- Fix the scope first: who calls this, how often, and what they do when it fails.
- Name the read and write paths separately; they rarely have the same bottleneck.
- Choose a partition key and say what query it makes expensive.
- State the consistency you need, and where you are willing to be stale.
Follow-up
- What breaks first when traffic grows ten times?
- How does this behave when that dependency is down for an hour?
Describe the difference between an abstract class and an interface, and give a practical use case for each.
Describe the difference between an abstract class and an interface, and give a practical use case for each.
Approach
- Clarify what is being asked and what a complete answer contains.
- State your assumptions explicitly before working the problem.
- Say what you would check first and why it is the highest-information step.
- Work from the requirement backwards to the design.
Follow-up
- What assumption would you test first?
- How would you know your answer was wrong?
Every query on one table stalls for forty seconds mid-deploy
During a release on PostgreSQL, every query touching resource times out for about 40 seconds and then recovers with no intervention. The release ran one migration, ALTER TABLE resource ADD COLUMN archived_reason TEXT, and the migration log shows it completing in 6 ms. Unrelated tables showed no change in error rate. Explain how a 6 ms statement caused a 40-second stall, give the ordered checks you would run on a live system to confirm it, and give the migration procedure that prevents a repeat.
Approach
- Separate the statement's duration from the lock's duration. ADD COLUMN with no default is a catalogue-only change and genuinely runs in milliseconds, but it requires ACCESS EXCLUSIVE, and it cannot acquire that until every transaction already touching the table has finished.
- Account for the queueing, which is the part that surprises people. A lock request that is waiting blocks later requests for conflicting modes behind it rather than letting them overtake, so one long-open transaction holds the DDL and the DDL holds all the traffic. The stall length is set by the longest open transaction, not by the size of the change.
- Confirm on a live system in this order: pg_stat_activity for that table ordered by xact_start, looking for the oldest transaction and specifically for state = idle in transaction; then pg_locks where granted = false to find the waiter; then join them on pid to name blocker and blocked. pg_blocking_pids() does that join for you and is the fastest single call.
- Prevent rather than merely time it better. Set lock_timeout to a second or two on the migration session so the DDL abandons the queue after a bounded wait and is retried, instead of holding it for as long as the oldest transaction lives. Be exact about what that buys: queries arriving during the wait still queue behind the pending ACCESS EXCLUSIVE request, so each attempt costs them up to one lock_timeout of added latency. The outage goes from 40 seconds to about one second per attempt, not to zero. Also run migrations away from deploy-time peaks, and put a statement timeout and an idle-in-transaction timeout on the analytics role that opens the long transactions.
Follow-up
- The same release also wants NOT NULL on that column. What is the sequence that gets there without a long lock?
- Your lock_timeout retry fails ten times in a row because the analytics transaction is always open. What do you change?
Built from the rounds and topics Optumrx candidates report.
Prepare, practise & reflect
One practical outcome each day. Spend longer where you need it.
0 / 7 done01Map the Optumrx loop
- Write out the reported sequence: Initial Hiring Manager Screen, Deep-Dive Technical Evaluations, Hybrid Technical-Managerial Discussion.
- For each round, write one sentence on what it is judging, from the description above, and mark the one you are least ready for.
Deliverable: A one-page map of the 3 reported rounds, with the weakest marked.
02Work React
- Spend the session on React, which Optumrx candidates report being tested on.
- Write one worked example in React and time yourself on it.
Deliverable: One timed worked example in React.
03Work React Hooks
- Spend the session on React Hooks, which Optumrx candidates report being tested on.
- Write one worked example in React Hooks and time yourself on it.
Deliverable: One timed worked example in React Hooks.
04Work Technical Interviewing
- Spend the session on Technical Interviewing, which Optumrx candidates report being tested on.
- Write one worked example in Technical Interviewing and time yourself on it.
Deliverable: One timed worked example in Technical Interviewing.
05Answer out loud: Frontend & React Development
- Answer aloud, timed: Build a functional React component (such as a search filter or interactive list) from scratch.
- Answer aloud, timed: Explain the difference between various React hooks (e.g., `useState`, `useEffect`, `useMemo`) and when to use them.
Deliverable: Spoken answers to 2 reported Frontend & React Development question(s), under time.
06Answer out loud: Core Programming & Object-Oriented Design
- Answer aloud, timed: What are the core pillars of Object-Oriented Programming (OOP), and how have you applied them in your recent projects?
- Answer aloud, timed: Explain the concept of dependency injection and why it is beneficial in enterprise applications.
Deliverable: Spoken answers to 2 reported Core Programming & Object-Oriented Design question(s), under time.
07Answer out loud: Databases & Query Design
- Answer aloud, timed: Write a SQL query to retrieve data across multiple tables using complex joins and aggregations.
- Answer aloud, timed: What is database normalization, and when might you intentionally denormalize a database schema?
Deliverable: Spoken answers to 2 reported Databases & Query Design question(s), under time.
Expand any day for tasks and deliverables. Your progress is saved on this device.
Behavioural rounds judge the decision you made and what it cost.
How do you handle event bubbling and capture in modern JavaScript?
How do you handle event bubbling and capture in modern JavaScript?
Approach
- Pick a story where you made the decision, not one where you watched it.
- State the situation in two sentences and spend the rest on the reasoning.
- Give the blast radius: what could have broken, and what you measured.
- Name the disagreement and how you resolved it with evidence.
Follow-up
- What would you do differently if you ran that again?
- How did you know your change caused the improvement?
Describe a time when you had to work with a difficult stakeholder or team member to deliver a project.
Describe a time when you had to work with a difficult stakeholder or team member to deliver a project.
Approach
- Pick a story where you made the decision, not one where you watched it.
- State the situation in two sentences and spend the rest on the reasoning.
- Give the blast radius: what could have broken, and what you measured.
- Name the disagreement and how you resolved it with evidence.
Follow-up
- What would you do differently if you ran that again?
- How did you know your change caused the improvement?
How do you handle technical debt when working under tight production deadlines?
How do you handle technical debt when working under tight production deadlines?
Approach
- Pick a story where you made the decision, not one where you watched it.
- State the situation in two sentences and spend the rest on the reasoning.
- Give the blast radius: what could have broken, and what you measured.
- Name the disagreement and how you resolved it with evidence.
Follow-up
- What would you do differently if you ran that again?
- How did you know your change caused the improvement?
Talk about a challenging technical bug you encountered in production and how you went about resolving it.
Talk about a challenging technical bug you encountered in production and how you went about resolving it.
Approach
- Pick a story where you made the decision, not one where you watched it.
- State the situation in two sentences and spend the rest on the reasoning.
- Give the blast radius: what could have broken, and what you measured.
- Name the disagreement and how you resolved it with evidence.
Follow-up
- What would you do differently if you ran that again?
- How did you know your change caused the improvement?
- 01
How do you handle event bubbling and capture in modern JavaScript?
- 02
Describe a time when you had to work with a difficult stakeholder or team member to deliver a project.
- 03
How do you handle technical debt when working under tight production deadlines?
- 04
Talk about a challenging technical bug you encountered in production and how you went about resolving it.
How difficult are the coding assessments at Optumrx?
The coding questions are generally rated as average in difficulty. They focus heavily on practical, real-world application building—such as creating UI components or writing SQL queries—rather than highly theoretical, complex algorithmic puzzles.
Optumrx Software Engineer candidate reports ↗What is the company culture like for engineers?
The culture is collaborative, supportive, and mission-driven. Engineers work closely together in agile teams, and there is a strong emphasis on work-life balance, continuous learning, and mutual support during technical challenges.
Optumrx Software Engineer candidate reports ↗How long does the entire interview process take?
The duration of the hiring process can vary, but it typically takes between two to four weeks from the initial recruiter screen to the final offer. The hiring team works hard to keep candidates informed at each stage of the progression.
Optumrx Software Engineer candidate reports ↗Does Optumrx support remote or hybrid working arrangements?
Yes, depending on the specific team and location, Optumrx offers flexible working models, including hybrid and fully remote opportunities for qualified engineering positions.
Optumrx Software Engineer candidate reports ↗What topics does Optumrx test in interviews?
Optumrx interviews most often cover Account Executive sales strategy, Pharmacy Benefits Management (PBM), Business Analysis, React, and Pharmacist Clinical Expertise. The exact emphasis depends on the specific role you apply for.
Optumrx Software Engineer candidate reports ↗Sources & methodology 3 sources ↗
No official company page is cited. Rounds and questions come from candidate reports and PracHub editorial material; each source shows the date it was read.
- 01Optumrx Software Engineer candidate reports ↗
Company-reported rounds, questions and FAQ.
Candidate reports · Accessed 2026-09-22 - 02PracHub Software Engineer practice ↗
PracHub practice material, not company-reported.
PracHub page · Accessed 2026-09-22 - 03PracHub preparation framework ↗
PracHub preparation guidance.
PracHub page · Accessed 2026-09-22
Explore related engineering environments and compare the preparation focus.
Vercel Software Engineer Interview Guide
Debugging practice for Vercel software engineer prep built on a reproduction you trust, narrowing to the smallest failing input, and changing one variable per run so the result stays attributable.
Spotify Software Engineer Interview Guide
Timed practice for Spotify software engineer candidates who lose time to the clock: short problems taken end to end, then reviewed against a written rubric rather than a passing test run.
Shopify Software Engineer Interview Guide
Timed practice for Shopify software engineer candidates who lose time to the clock: short problems taken end to end, then reviewed against a written rubric rather than a passing test run.
Ramp Software Engineer Interview Guide
Systems practice for Ramp software engineer candidates, weighted toward payments and lending work: the load that actually arrives, the failure modes that matter there, and the invariants a partial outage must not break.