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Hudl Software Engineer Interview Guide

Hudl Software Engineer interview guide: reported rounds, questions and how candidates describe the process.

The 60-second brief

As a Software Engineer at Hudl, you play a vital role in transforming how coaches, athletes, and sports organizations capture, analyze, and leverage video and performance data. Hudl powers sports teams globally across every level—from youth leagues and high schools to elite professional organizations—helping them see their game differently. You will work on foundational products across diverse domain spaces, including real-time video livestreaming, high-throughput analytics pipelines, athlete tracking, automated tagging, and ticketing services. Engineering at Hudl is built on speed, autonomy, and cross-functional ownership. You will be integrated into a dedicated squad alongside Product Managers, Designers, Quality Assurance Engineers, and Scrum Masters.

This guide is scoped to a Software Engineer candidate at Hudl.

Focus areas

  • Behavioral Interviews
  • Communication Skills (Technical + Verbal)
  • System Design

The Hudl interview process

Hudl candidates report 4 rounds over 3-5 weeks. The stages below are what candidates describe, not a published process.

Recruiter Screen

Initial discussion to align on your background and interest in the role.

What to demonstrate

  • Initial discussion to align on your background and interest in the role
  • Depth in Behavioral Interviews

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.

Technical Screen

May involve a take-home project or a live coding session based on seniority and team.

What to demonstrate

  • May involve a take-home project or a live coding session based on seniority and team
  • Depth in Behavioral Interviews

How to prepare

  • Answer aloud and timed: Design an algorithm that simulates match progression or game scoring while tracking edge-case state changes accurately.
  • Answer aloud and timed: Implement a memory-efficient algorithm to format and filter user activity feeds under strict execution constraints.

Code Review

Walk through your solution from the take-home project, explaining design choices.

What to demonstrate

  • Walk through your solution from the take-home project, explaining design choices
  • Depth in Behavioral Interviews

How to prepare

  • Answer aloud and timed: Solve an array manipulation problem focusing on time and space complexity while explaining your trade-offs clearly to your interviewer.
  • Answer aloud and timed: Walk us through the asynchronous technical assessment you completed. What edge cases did you account for, and how would you refactor your solution for production scale?

Virtual Onsite Loop

Series of interviews focusing on technical expertise, system design, and behavioral alignment.

What to demonstrate

  • Series of interviews focusing on technical expertise, system design, and behavioral alignment
  • Depth in Behavioral Interviews

How to prepare

  • Answer aloud and timed: How do you balance rapid delivery cycles with writing clean, testable, and maintainable software?
  • Answer aloud and timed: Explain how you would add automated test coverage to an existing API endpoint that lacks integration testing.

Where candidates lose points

Prepare detailed behavioral examples using the STAR method

Be ready with specific anecdotes highlighting how you worked through technical trade-offs, collaborated with cross-functional squad members, and handled changing project scopes.

Be ready to walk through your code step-by-step

During the technical interview, practice explaining your thought process, why you chose specific data structures, and how you would handle potential edge cases or production bugs.

Show strong user and product focus

Hudl engineers work closely with product teams to solve real coach and athlete problems. Frame your technical answers around business outcomes, end-user experience, and system reliability.

Questions & practice

Write a program to parse and order an event stream of sports telemetry data, handling missing timestamp attrib

Medium · Coding & Problem-Solving

Write a program to parse and order an event stream of sports telemetry data, handling missing timestamp attributes and out-of-order sequences.

Approach

  1. Restate the input: its shape, its size, and what is guaranteed about it.
  2. Name the brute-force solution and its complexity before improving on it.
  3. Choose the data structure from the access pattern, not from familiarity.
  4. 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?

Given an array of athlete score performance metrics, implement an efficient two-pointer solution to find peak

Medium · Coding & Problem-Solving

Given an array of athlete score performance metrics, implement an efficient two-pointer solution to find peak performance windows.

Approach

  1. Say what the runtime actually does before reasoning about the code.
  2. Name what is shared across threads and what owns each piece of state.
  3. Identify the window where an invariant is briefly untrue.
  4. Distinguish a value from a reference to it, and say which one you handed out.

Follow-up

  • What happens if two callers reach this at the same time?
  • Where could this allocate more than you expect?

Implement a memory-efficient algorithm to format and filter user activity feeds under strict execution constra

Medium · Coding & Problem-Solving

Implement a memory-efficient algorithm to format and filter user activity feeds under strict execution constraints.

Approach

  1. Say what the runtime actually does before reasoning about the code.
  2. Name what is shared across threads and what owns each piece of state.
  3. Identify the window where an invariant is briefly untrue.
  4. Distinguish a value from a reference to it, and say which one you handed out.

Follow-up

  • What happens if two callers reach this at the same time?
  • Where could this allocate more than you expect?

Solve an array manipulation problem focusing on time and space complexity while explaining your trade-offs cle

Medium · Coding & Problem-Solving

Solve an array manipulation problem focusing on time and space complexity while explaining your trade-offs clearly to your interviewer.

Approach

  1. Restate the input: its shape, its size, and what is guaranteed about it.
  2. Name the brute-force solution and its complexity before improving on it.
  3. Choose the data structure from the access pattern, not from familiarity.
  4. 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?

Walk us through the asynchronous technical assessment you completed. What edge cases did you account for, and

Medium · Technical Walkthrough & Code Quality

Walk us through the asynchronous technical assessment you completed. What edge cases did you account for, and how would you refactor your solution for production scale?

Approach

  1. Say what the runtime actually does before reasoning about the code.
  2. Name what is shared across threads and what owns each piece of state.
  3. Identify the window where an invariant is briefly untrue.
  4. Distinguish a value from a reference to it, and say which one you handed out.

Follow-up

  • What happens if two callers reach this at the same time?
  • Where could this allocate more than you expect?

How do you approach working with Quality Assurance, Product, and Design team members to break down ambiguous p

Medium · Behavioral & Team Collaboration

How do you approach working with Quality Assurance, Product, and Design team members to break down ambiguous product requirements?

Approach

  1. Restate the input: its shape, its size, and what is guaranteed about it.
  2. Name the brute-force solution and its complexity before improving on it.
  3. Choose the data structure from the access pattern, not from familiarity.
  4. 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?

How do you approach database indexing, caching strategies, and query optimization for high-traffic read operat

Medium · System Design & Architecture

How do you approach database indexing, caching strategies, and query optimization for high-traffic read operations?

Approach

  1. Name the grain you start from and join outward from it.
  2. Check whether any join is one-to-many before aggregating, or the sums inflate.
  3. Say which index the query would use, and what makes it unusable.
  4. 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?

Stop tag and share joins from fanning out a page

Medium · join fan-out · semi-joins · many-to-many

resource_tag is (resource_id, tag_id) with PK (resource_id, tag_id); resource_share is (resource_id, shared_with_user_id, permission). The tagged-and-shared listing inner-joins resource to both, filters tenant_id, tag_id = ANY($2) and shared_with_user_id = $3, orders by updated_at DESC and takes 50. Pages come back with fewer than 50 distinct resources and the total in the header is far too high. Explain the row multiplication, rewrite both the page query and the count query so each is correct, and name the index each one needs. PostgreSQL 16.

Approach

  1. Do the arithmetic against the predicates that are actually there. An inner join emits one row per matching child row, and both joins are filtered: tag_id = ANY($2) admits only the requested tags, shared_with_user_id = $3 admits one user's share rows. So a resource holding three of the requested tags and shared with $3 once yields three rows, not one — the multiplier is its count of matching tags times its share rows for that single user, and that second factor is 1 unless the table admits duplicate (resource_id, shared_with_user_id) pairs. LIMIT 50 then limits rows rather than resources, and COUNT(*) counts pairs — the header is the product, not the population.
  2. Reject DISTINCT as the fix. It deduplicates after the product has been built, so the planner must materialise and sort the fanned-out set before the LIMIT can apply, and it leaves any SUM or AVG in the same select list wrong.
  3. Rewrite both filters as semi-joins, keeping resource as the only row source: AND EXISTS (SELECT 1 FROM resource_tag rt WHERE rt.resource_id = r.resource_id AND rt.tag_id = ANY($2)) and the same shape against resource_share. A semi-join stops at the first match per resource and preserves the driving index order, so ORDER BY updated_at DESC, resource_id DESC LIMIT 50 still stops after 50 rows.
  4. Count with the same predicates and no join at all: SELECT count(*) FROM resource r WHERE r.tenant_id = $1 AND r.status = 'active' AND EXISTS (...) AND EXISTS (...). Nothing multiplies a resource, so the number is the population.

Follow-up

  • The filter changes from 'any of these tags' to 'all of these tags'. Rewrite it and state what it costs relative to the ANY form.
  • A resource can be shared with the same user twice under different permissions. Does your count change, and should it?

Design an algorithm that simulates match progression or game scoring while tracking edge-case state changes ac

Medium · Coding & Problem-Solving

Design an algorithm that simulates match progression or game scoring while tracking edge-case state changes accurately.

Approach

  1. Fix the scope first: who calls this, how often, and what they do when it fails.
  2. Name the read and write paths separately; they rarely have the same bottleneck.
  3. Choose a partition key and say what query it makes expensive.
  4. 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?

How do you balance rapid delivery cycles with writing clean, testable, and maintainable software?

Medium · Technical Walkthrough & Code Quality

Approach

  1. Clarify what is being asked and what a complete answer contains.
  2. State your assumptions explicitly before working the problem.
  3. Say what you would check first and why it is the highest-information step.
  4. 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 would add automated test coverage to an existing API endpoint that lacks integration testing.

Medium · Technical Walkthrough & Code Quality

Approach

  1. Say who the caller is and what they do when the call fails halfway.
  2. Define the identity of a request so a retry cannot double-apply it.
  3. Separate accepted, pending, failed and confirmed; they are different facts.
  4. 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?

What considerations do you take into account when defining data contracts or DTOs between backend services and

Medium · Technical Walkthrough & Code Quality

What considerations do you take into account when defining data contracts or DTOs between backend services and client interfaces?

Approach

  1. Clarify what is being asked and what a complete answer contains.
  2. State your assumptions explicitly before working the problem.
  3. Say what you would check first and why it is the highest-information step.
  4. 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 would you design a backend API to serve personalized video feeds for hundreds of thousands of concurrent f

Medium · System Design & Architecture

How would you design a backend API to serve personalized video feeds for hundreds of thousands of concurrent fans during live tournament broadcasts?

Approach

  1. Fix the scope first: who calls this, how often, and what they do when it fails.
  2. Name the read and write paths separately; they rarely have the same bottleneck.
  3. Choose a partition key and say what query it makes expensive.
  4. 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?

Walk through the architecture of a high-throughput processing pipeline that ingests raw telemetry data and out

Medium · System Design & Architecture

Walk through the architecture of a high-throughput processing pipeline that ingests raw telemetry data and outputs actionable analytics in near real-time.

Approach

  1. Fix the scope first: who calls this, how often, and what they do when it fails.
  2. Name the read and write paths separately; they rarely have the same bottleneck.
  3. Choose a partition key and say what query it makes expensive.
  4. 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?

How do you choose between relational and non-relational storage when designing data persistence layers for sca

Medium · System Design & Architecture

How do you choose between relational and non-relational storage when designing data persistence layers for scalable microservices?

Approach

  1. Fix the scope first: who calls this, how often, and what they do when it fails.
  2. Name the read and write paths separately; they rarely have the same bottleneck.
  3. Choose a partition key and say what query it makes expensive.
  4. 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 your strategy for managing microservice communication and event streaming using asynchronous messagin

Medium · System Design & Architecture

Describe your strategy for managing microservice communication and event streaming using asynchronous messaging brokers.

Approach

  1. Fix the scope first: who calls this, how often, and what they do when it fails.
  2. Name the read and write paths separately; they rarely have the same bottleneck.
  3. Choose a partition key and say what query it makes expensive.
  4. 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?

Edge instances grow 400 MB per hour until the nightly restart

Hard · memory leak · heap analysis · metric cardinality

Edge API instances start at 700 MB resident and grow about 400 MB/hour; a nightly rolling restart has hidden it for weeks. Growth continues unchanged when request rate halves overnight, p99 degrades in the last hours before an instance is recycled, and heap used immediately after a forced full GC rises monotonically. The service holds no product state. Name the discriminating measurement that separates the plausible causes, give the most likely cause, and give the fix and how you would verify it.

Approach

  1. Separate resident memory from live heap first, because they fail differently. Resident size can grow from fragmentation, native buffers or thread stacks while the heap is flat; heap used after a full GC rising monotonically is the measurement that says objects are reachable and not being released. You already have it, so this is retention, not fragmentation, and that closes off half the candidate list.
  2. Use the rate's independence from traffic as the discriminator. Growth that continues at half the request rate rules out per-request objects that are merely slow to collect and points at a structure that grows with distinct values observed rather than with call volume. Write the candidates that have that property: a metrics registry keyed on a high-cardinality label, an unevicted cache, an interner, a per-key lock map.
  3. Take two heap snapshots an hour apart and diff by retained size, reading the dominator tree, not by allocation count or instance count. Expect one root holding a map with millions of entries, then follow the reference chain to the code that inserts and never removes. Allocation profilers point at churn, which is the wrong signal here.
  4. The candidate that fits this service is an observability label carrying an identifier, such as a request path recorded before templating so that /v1/resources/48213 becomes its own metric series. That grows with distinct ids seen, is independent of rate, and explains the late p99 degradation, since GC cost rises with the size of the live set.

Follow-up

  • Post-GC heap is now flat but resident size still creeps. What are you looking at, and does it matter?
  • How would you have detected this before an OOM, given the nightly restart masked the trend?

Suggested practice checklist

Built from the rounds and topics Hudl candidates report.

Day 1 — Map the Hudl loop

  • Write out the reported sequence: Recruiter Screen, Technical Screen, Code Review, Virtual Onsite 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 4 reported rounds, with the weakest marked.

Day 2 — Work Behavioral Interviews

  • Spend the session on Behavioral Interviews, which Hudl candidates report being tested on.
  • Write one worked example in Behavioral Interviews and time yourself on it.

Deliverable: One timed worked example in Behavioral Interviews.

Day 3 — Work Communication Skills (Technical + Verbal)

  • Spend the session on Communication Skills (Technical + Verbal), which Hudl candidates report being tested on.
  • Write one worked example in Communication Skills (Technical + Verbal) and time yourself on it.

Deliverable: One timed worked example in Communication Skills (Technical + Verbal).

Day 4 — Work System Design

  • Spend the session on System Design, which Hudl candidates report being tested on.
  • Write one worked example in System Design and time yourself on it.

Deliverable: One timed worked example in System Design.

Day 5 — Answer out loud: Coding & Problem-Solving

  • Answer aloud, timed: Write a program to parse and order an event stream of sports telemetry data, handling missing timestamp attributes and out-of-order sequences.
  • Answer aloud, timed: Given an array of athlete score performance metrics, implement an efficient two-pointer solution to find peak performance windows.

Deliverable: Spoken answers to 2 reported Coding & Problem-Solving question(s), under time.

Day 6 — Answer out loud: Technical Walkthrough & Code Quality

  • Answer aloud, timed: Walk us through the asynchronous technical assessment you completed. What edge cases did you account for, and how would you refactor your solution for production scale?
  • Answer aloud, timed: How do you balance rapid delivery cycles with writing clean, testable, and maintainable software?

Deliverable: Spoken answers to 2 reported Technical Walkthrough & Code Quality question(s), under time.

Day 7 — Answer out loud: System Design & Architecture

  • Answer aloud, timed: How would you design a backend API to serve personalized video feeds for hundreds of thousands of concurrent fans during live tournament broadcasts?
  • Answer aloud, timed: Walk through the architecture of a high-throughput processing pipeline that ingests raw telemetry data and outputs actionable analytics in near real-time.

Deliverable: Spoken answers to 2 reported System Design & Architecture question(s), under time.

Behavioural preparation

Behavioural rounds judge the decision you made and what it cost.

Describe a time when you received feedback on a pull request that challenged your approach. How did you handle

Medium · Technical Walkthrough & Code Quality

Describe a time when you received feedback on a pull request that challenged your approach. How did you handle the conversation?

Approach

  1. Pick a story where you made the decision, not one where you watched it.
  2. State the situation in two sentences and spend the rest on the reasoning.
  3. Give the blast radius: what could have broken, and what you measured.
  4. 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 a time you had to resolve a technical disagreement with a squad teammate or product owner. What

Medium · Behavioral & Team Collaboration

Tell me about a time you had to resolve a technical disagreement with a squad teammate or product owner. What was the outcome?

Approach

  1. Pick a story where you made the decision, not one where you watched it.
  2. State the situation in two sentences and spend the rest on the reasoning.
  3. Give the blast radius: what could have broken, and what you measured.
  4. 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 challenging project where requirements changed midway through development. How did you adapt and ke

Medium · Behavioral & Team Collaboration

Describe a challenging project where requirements changed midway through development. How did you adapt and keep the team aligned?

Approach

  1. Pick a story where you made the decision, not one where you watched it.
  2. State the situation in two sentences and spend the rest on the reasoning.
  3. Give the blast radius: what could have broken, and what you measured.
  4. 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?

Can you give an example of how you mentor junior engineers or elevate engineering practices within your team?

Medium · Behavioral & Team Collaboration

Approach

  1. Pick a story where you made the decision, not one where you watched it.
  2. State the situation in two sentences and spend the rest on the reasoning.
  3. Give the blast radius: what could have broken, and what you measured.
  4. 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 a production deployment caused an issue. How did you handle post-incident response

Medium · Behavioral & Team Collaboration

Describe a situation where a production deployment caused an issue. How did you handle post-incident response and prevention?

Approach

  1. Pick a story where you made the decision, not one where you watched it.
  2. State the situation in two sentences and spend the rest on the reasoning.
  3. Give the blast radius: what could have broken, and what you measured.
  4. 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?