A Software Engineer at Pagerduty is responsible for building and scaling the digital operations management platform that thousands of global enterprises rely on to keep their critical systems online. When digital services fail, Pagerduty is the central nervous system that orchestrates the response. Consequently, the software you write here directly impacts system reliability and incident response times for major platforms worldwide. Engineers at Pagerduty tackle complex, high-throughput distributed systems challenges, working on real-time event routing, advanced scheduling algorithms, and high-availability infrastructure. Whether you join the Core Product team, the Authorization Team, or the HR Infrastructure & Operations group, your work will focus on resilience, low-latency execution, and seamless user experiences. This role demands a unique combination of disciplined systems thinking and practical, hands-on execution. Because Pagerduty engineers participate in on-call rotations and manage their own services, the engineering culture values operational excellence, clean code extensibility, and pragmatic problem-solving over theoretical puzzle-solving.
Recruiter Screen
reportedInitial discussion to align on your background, salary expectations, and interest in the company.
What to demonstrate
- Initial discussion to align on your background, salary expectations, and interest in the company
- Depth in Algorithms & Data Structures
How to prepare
- Be able to walk your CV end to end in two minutes, and say why this company specifically.
- Have your salary expectations, notice period and location constraints ready, and ask for the rest of the loop in writing.
Hiring Manager Call
reportedCall focusing on your career history, technical achievements, and behavioral scenarios.
What to demonstrate
- Call focusing on your career history, technical achievements, and behavioral scenarios
- Depth in Algorithms & Data Structures
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.
Take-Home Coding Assignment
reportedBuild a small, functional application (MVP) in the language of your choice.
What to demonstrate
- Build a small, functional application (MVP) in the language of your choice
- Depth in Algorithms & Data Structures
How to prepare
- Answer aloud and timed: Expand a pre-built skeleton application to integrate with an external API, demonstrating how you handle network failures and asynchronous data parsing.
- Answer aloud and timed: Design a real-time notification dispatch system capable of routing alerts via SMS, email, and push notifications with strict rate-limiting.
Live Collaborative Session
reportedPair with an engineer to expand upon your take-home code.
What to demonstrate
- Pair with an engineer to expand upon your take-home code
- Depth in Algorithms & Data Structures
How to prepare
- Answer aloud and timed: Model a database schema for a complex multi-tenant authorization system, explaining your choice of indexes and foreign keys.
- Answer aloud and timed: Architect an API gateway that handles high-throughput traffic, detailing how you would manage authentication, caching, and failover.
Onsite/Virtual Loop
reportedComprehensive evaluation of system design, data modeling, and behavioral fit.
What to demonstrate
- Comprehensive evaluation of system design, data modeling, and behavioral fit
- Depth in Algorithms & Data Structures
How to prepare
- Answer aloud and timed: Design a high-volume data pipeline that ingests system metrics, aggregates them in real time, and stores them for historical analysis.
- Answer aloud and timed: Explain how you would migrate a monolithic user service to a microservices architecture without causing downtime for active users.
PracHub editorial advice for the preparation topics above.
Treat the Take-Home Seriously
The take-home MVP is not just a screening filter; it forms the entire foundation of your subsequent live coding round. Write clean, well-structured, and thoroughly commented code. Ensure you have robust error handling and basic test coverage in place.
Do not rush through the take-home MVP assignment
If your base code is messy or lacks structure, you will find it incredibly difficult to add the requested live features during the high-pressure, 60-minute collaborative coding interview.
Think Out Loud
During both the pair-programming and system design rounds, your interviewers are evaluating your thought process and communication style. Explain your assumptions, voice any trade-offs you are considering, and clarify requirements before writing code or drawing diagrams.
Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.
Write a program that reads a dataset of key-value pairs and find specific combinations that sum to a target va
Write a program that reads a dataset of key-value pairs and find specific combinations that sum to a target value, ensuring optimal time and space complexity.
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?
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?
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?
Model a database schema for a complex multi-tenant authorization system, explaining your choice of indexes and
Model a database schema for a complex multi-tenant authorization system, explaining your choice of indexes and foreign keys.
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?
Write a SQL query utilizing complex joins and aggregations to count active incident records across multiple ta
Write a SQL query utilizing complex joins and aggregations to count active incident records across multiple tables based on specific regional criteria.
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?
Build a minimal viable product (MVP) for a cookbook/recipe application, then add live features to filter recip
Build a minimal viable product (MVP) for a cookbook/recipe application, then add live features to filter recipes by ingredients or calculate total preparation time.
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?
Implement a basic task management (todo) application, and subsequently refactor it to support prioritized queu
Implement a basic task management (todo) application, and subsequently refactor it to support prioritized queues and nested sub-tasks.
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?
Create a configuration parser that validates nested brackets or parentheses, ensuring the input is structurall
Create a configuration parser that validates nested brackets or parentheses, ensuring the input is structurally sound.
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?
Expand a pre-built skeleton application to integrate with an external API, demonstrating how you handle networ
Expand a pre-built skeleton application to integrate with an external API, demonstrating how you handle network failures and asynchronous data parsing.
Approach
- Say who the caller is and what they do when the call fails halfway.
- Define the identity of a request so a retry cannot double-apply it.
- Separate accepted, pending, failed and confirmed; they are different facts.
- Design the error taxonomy before the success shape; callers branch on it.
Follow-up
- What happens if the caller retries after a timeout?
- How does a client discover it is on an old version of this contract?
Design a real-time notification dispatch system capable of routing alerts via SMS, email, and push notificatio
Design a real-time notification dispatch system capable of routing alerts via SMS, email, and push notifications with strict rate-limiting.
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?
Architect an API gateway that handles high-throughput traffic, detailing how you would manage authentication,
Architect an API gateway that handles high-throughput traffic, detailing how you would manage authentication, caching, and failover.
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?
Design a high-volume data pipeline that ingests system metrics, aggregates them in real time, and stores them
Design a high-volume data pipeline that ingests system metrics, aggregates them in real time, and stores them for historical analysis.
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?
Explain how you would migrate a monolithic user service to a microservices architecture without causing downti
Explain how you would migrate a monolithic user service to a microservices architecture without causing downtime for active users.
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?
You are logged into a remote Linux server that is experiencing high latency. Walk through the command-line too
You are logged into a remote Linux server that is experiencing high latency. Walk through the command-line tools and steps you would use to identify the bottleneck.
Approach
- Establish what changed and when, before forming any theory.
- Pick a bisection that eliminates candidates whichever way it turns out.
- Check the instrumentation before believing the symptom.
- Separate the trigger from the cause; the deploy is rarely the bug.
Follow-up
- What would you look at first, and what would it rule out?
- How would you tell a cause from a coincidence here?
Configure and start a caching daemon (such as Memcached) from the command line, and explain how you would veri
Configure and start a caching daemon (such as Memcached) from the command line, and explain how you would verify its operational statistics.
Approach
- Establish what changed and when, before forming any theory.
- Pick a bisection that eliminates candidates whichever way it turns out.
- Check the instrumentation before believing the symptom.
- Separate the trigger from the cause; the deploy is rarely the bug.
Follow-up
- What would you look at first, and what would it rule out?
- How would you tell a cause from a coincidence here?
Walk through how you would diagnose a database connection pool exhaustion issue in a production environment.
Walk through how you would diagnose a database connection pool exhaustion issue in a production environment.
Approach
- Establish what changed and when, before forming any theory.
- Pick a bisection that eliminates candidates whichever way it turns out.
- Check the instrumentation before believing the symptom.
- Separate the trigger from the cause; the deploy is rarely the bug.
Follow-up
- What would you look at first, and what would it rule out?
- How would you tell a cause from a coincidence here?
Explain the trade-offs between relational databases and NoSQL databases when storing high-frequency event logs
Explain the trade-offs between relational databases and NoSQL databases when storing high-frequency event logs.
Approach
- Establish what changed and when, before forming any theory.
- Pick a bisection that eliminates candidates whichever way it turns out.
- Check the instrumentation before believing the symptom.
- Separate the trigger from the cause; the deploy is rarely the bug.
Follow-up
- What would you look at first, and what would it rule out?
- How would you tell a cause from a coincidence here?
Built from the rounds and topics Pagerduty candidates report.
Prepare, practise & reflect
One practical outcome each day. Spend longer where you need it.
0 / 7 done01Map the Pagerduty loop
- Write out the reported sequence: Recruiter Screen, Hiring Manager Call, Take-Home Coding Assignment, Live Collaborative Session, Onsite/Virtual Loop.
- 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 5 reported rounds, with the weakest marked.
02Work Algorithms & Data Structures
- Spend the session on Algorithms & Data Structures, which Pagerduty candidates report being tested on.
- Write one worked example in Algorithms & Data Structures and time yourself on it.
Deliverable: One timed worked example in Algorithms & Data Structures.
03Work Building an MVP / Starter App
- Spend the session on Building an MVP / Starter App, which Pagerduty candidates report being tested on.
- Write one worked example in Building an MVP / Starter App and time yourself on it.
Deliverable: One timed worked example in Building an MVP / Starter App.
04Work Technical Communication / Explaining Thought Process
- Spend the session on Technical Communication / Explaining Thought Process, which Pagerduty candidates report being tested on.
- Write one worked example in Technical Communication / Explaining Thought Process and time yourself on it.
Deliverable: One timed worked example in Technical Communication / Explaining Thought Process.
05Answer out loud: Application Development & Live Refactoring
- Answer aloud, timed: Build a minimal viable product (MVP) for a cookbook/recipe application, then add live features to filter recipes by ingredients or calculate total preparation time.
- Answer aloud, timed: Implement a basic task management (todo) application, and subsequently refactor it to support prioritized queues and nested sub-tasks.
Deliverable: Spoken answers to 2 reported Application Development & Live Refactoring question(s), under time.
06Answer out loud: System Design & Data Modeling
- Answer aloud, timed: Design a real-time notification dispatch system capable of routing alerts via SMS, email, and push notifications with strict rate-limiting.
- Answer aloud, timed: Model a database schema for a complex multi-tenant authorization system, explaining your choice of indexes and foreign keys.
Deliverable: Spoken answers to 2 reported System Design & Data Modeling question(s), under time.
07Answer out loud: Systems Troubleshooting & Operations
- Answer aloud, timed: You are logged into a remote Linux server that is experiencing high latency. Walk through the command-line tools and steps you would use to identify the bottleneck.
- Answer aloud, timed: Write a SQL query utilizing complex joins and aggregations to count active incident records across multiple tables based on specific regional criteria.
Deliverable: Spoken answers to 2 reported Systems Troubleshooting & Operations 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.
Describe a time when you made a significant technical mistake in a production system. How did you identify it,
Describe a time when you made a significant technical mistake in a production system. How did you identify it, resolve it, and what did you learn?
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?
Tell me about the largest or most complex engineering team you have worked on. How did you manage communicatio
Tell me about the largest or most complex engineering team you have worked on. How did you manage communication and technical alignment?
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 situation where you had a strong technical disagreement with a peer or manager. How did you resolve
Describe a situation where you had a strong technical disagreement with a peer or manager. How did you resolve it to keep the project moving forward?
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?
Who was the best mentor you ever had, and what specific qualities made them effective?
Who was the best mentor you ever had, and what specific qualities made them effective?
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?
Why do you want to work at Pagerduty, and how do you approach maintaining system reliability during your own o
Why do you want to work at Pagerduty, and how do you approach maintaining system reliability during your own on-call shifts?
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
Describe a time when you made a significant technical mistake in a production system. How did you identify it, resolve it, and what did you learn?
- 02
Tell me about the largest or most complex engineering team you have worked on. How did you manage communication and technical alignment?
- 03
Describe a situation where you had a strong technical disagreement with a peer or manager. How did you resolve it to keep the project moving forward?
- 04
Who was the best mentor you ever had, and what specific qualities made them effective?
Can I use my own laptop and development environment for the coding interviews?
Yes. Pagerduty encourages you to use your own laptop, IDE, operating system, and preferred programming language during the technical interviews. They want you to be as comfortable and productive as possible, reflecting how you would actually work on the job.
Pagerduty Software Engineer candidate reports ↗How much LeetCode-style algorithmic memorization is required?
Very little. While you should understand basic data structures (such as arrays, hash maps, queues, and stacks) and their time complexities, Pagerduty avoids highly abstract algorithmic puzzles. The technical interviews focus heavily on practical application development, code refactoring, system design, and real-world troubleshooting.
Pagerduty Software Engineer candidate reports ↗What is the engineering culture like regarding on-call responsibilities?
Pagerduty practices a "you build it, you run it" philosophy. Engineering teams own their services end-to-end, which includes participating in on-call rotations. Because they build the very tool used for incident response, the engineering team is highly disciplined about system reliability, automated testing, and minimizing operational noise.
Pagerduty Software Engineer candidate reports ↗How long does the interview process take from start to finish?
The entire process typically takes between three to four weeks. Recruiters are generally highly responsive, frequently reaching out within a day or two of each interview stage to schedule the next step.
Pagerduty Software Engineer candidate reports ↗Are there hybrid or remote work expectations for this position?
This depends on the specific team and office location (such as San Francisco, Atlanta, Toronto, or Lisbon). Pagerduty supports a variety of working models, including hybrid setups for offices and fully remote roles for specific teams. You should clarify your preferred working model with your recruiter during the initial screen.
Pagerduty Software Engineer candidate reports ↗What topics does Pagerduty test in interviews?
Pagerduty interviews most often cover Behavioral Interviewing, Stakeholder Management, Cross-Functional Collaboration, Data Analysis, and SQL. The exact emphasis depends on the specific role you apply for.
Pagerduty 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.
- 01Pagerduty 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.
Cognition Software Engineer Interview Guide
What Cognition asks Software Engineer candidates, from reported rounds and questions.
Discord Software Engineer Interview Guide
Database practice for Discord candidates: how an index changes a query plan, and which anomalies survive a given isolation level, since read committed still permits non-repeatable reads.
CoreWeave Software Engineer Interview Guide
Failure-handling practice for CoreWeave software engineer candidates: requests whose outcome a timeout leaves unknown, where a retry is safe, and deduplicating at the receiver instead of assuming exactly-once delivery.
Aerospike Software Engineer Interview Questions & Guide 2026
Aerospike database-engine preparation through an original single-owner Python key-value store with bounded logical index accounting, disk-offset reads, conditional writes, tombstones, process-restart recovery and 3,240 checks. Existing 14 p