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Planet Software Engineer Interview Guide

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

The 60-second brief

A Software Engineer at Planet plays a critical role in designing, building, and scaling the infrastructure that processes massive volumes of geospatial data and satellite imagery. At Planet, software engineering is not just about writing clean code; it is about managing complex, distributed pipelines that ingest, process, and deliver high-resolution imagery of the entire Earth daily. Your work directly impacts global industries, environmental researchers, and humanitarian organizations who rely on this data to make critical, real-time decisions. As a member of the engineering team, you will contribute to high-performance computing systems, cloud-native architectures, and robust APIs.

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

Focus areas

  • Technical Interviewing
  • Coding (Live/Real-Time Coding)
  • Networking Knowledge

The Planet interview process

Planet candidates report 5 rounds over 4-6 weeks. The stages below are what candidates describe, not a published process.

HR Phone Screening

Initial call focusing on your professional background, career motivations, and alignment with the role.

What to demonstrate

  • Initial call focusing on your professional background, career motivations, and alignment with the role
  • Depth in Technical Interviewing

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 Evaluation

Technical and scenario-based video interview with engineering staff discussing past experiences and system design principles.

What to demonstrate

  • Technical and scenario-based video interview with engineering staff discussing past experiences and system design principles
  • Depth in Technical Interviewing

How to prepare

  • Answer aloud and timed: Describe your experience with networking protocols and how they relate to distributing large media files or video streams.
  • Answer aloud and timed: How would you design a system to monitor network latency across geographically distributed data centers?

Live Coding Interview

Real-time coding session with engineers to assess coding proficiency and problem-solving speed.

What to demonstrate

  • Real-time coding session with engineers to assess coding proficiency and problem-solving speed
  • Depth in Technical Interviewing

How to prepare

  • Answer aloud and timed: Write a function to detect cycles in a directed graph, and explain its time and space complexity.
  • Answer aloud and timed: How would you parse and process a continuous stream of coordinate data from a satellite without exhausting system memory?

Hiring Manager Meeting

Discussion with the hiring manager to align on team expectations.

What to demonstrate

  • Discussion with the hiring manager to align on team expectations
  • Depth in Technical Interviewing

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.

Final HR Round

Final discussion with HR regarding compensation and logistics.

What to demonstrate

  • Final discussion with HR regarding compensation and logistics
  • Depth in Technical Interviewing

How to prepare

  • Prepare three examples from your own work, each with a decision you made and an outcome you can quantify.
  • Re-read the description of the final hr round above and write down what you would ask to confirm before it.

Where candidates lose points

Practice live coding out loud

The live coding round can feel high-pressure. Practice writing code on a shared document or IDE while explaining your logic, assumptions, and trade-offs in real time.

Brush up on networking fundamentals

Do not overlook networking. Be ready to discuss protocols, packet routing, and data transmission, as these are critical to Planet's satellite communication and data delivery pipelines.

Structure your behavioral answers

Use the STAR method (Situation, Task, Action, Result) to keep your answers concise and impactful. Focus heavily on your personal actions and the measurable outcomes of your projects.

Questions & practice

Write a function to detect cycles in a directed graph, and explain its time and space complexity.

Medium · Coding & Problem Solving

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 would you parse and process a continuous stream of coordinate data from a satellite without exhausting sys

Medium · Coding & Problem Solving

How would you parse and process a continuous stream of coordinate data from a satellite without exhausting system memory?

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?

Given a large, unsorted dataset of geographical coordinates, design an efficient algorithm to find the closest

Medium · Coding & Problem Solving

Given a large, unsorted dataset of geographical coordinates, design an efficient algorithm to find the closest points of interest.

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?

Hold a per-tenant active cap against concurrent creates

Hard · write skew · isolation levels · constraints

A tenant on the standard plan may hold at most 50 resources with status='active'. The create handler runs SELECT count(*) FROM resource WHERE tenant_id = $1 AND status = 'active', compares to 50, then inserts. Two creates arrive 3 ms apart on different instances and the tenant lands at 51. Name the anomaly, say whether PostgreSQL 16 READ COMMITTED or REPEATABLE READ prevents it and why, then give an implementation that holds the cap at READ COMMITTED with the exact statements. Finally, say what changes when the cap is 'at most one running export per tenant' on job_run.

Approach

  1. Name it: write skew. The two transactions read an overlapping set and write disjoint rows, so there is no row-level conflict for the engine to detect and each commit is individually legal.
  2. Rule out the levels precisely. READ COMMITTED takes a fresh snapshot per statement and takes no lock on the counted rows, so both see 49. PostgreSQL's REPEATABLE READ is snapshot isolation: it removes non-repeatable reads and phantoms within the snapshot but still admits write skew, because the anomaly is not a re-read of a changed row, it is a read of a set that a concurrent transaction invalidates. Only SERIALIZABLE closes it, by tracking the read dependency and aborting one transaction with SQLSTATE 40001 — a guarantee that exists only if the application re-runs the whole transaction from the read.
  3. Convert the set predicate into a single-row conflict: keep tenant.active_resource_count and run UPDATE tenant SET active_resource_count = active_resource_count + 1 WHERE tenant_id = $1 AND active_resource_count < 50 in the same transaction as the INSERT. Zero affected rows is the cap, returned as 409. The row lock serialises the decision at any isolation level, and contention is bounded to one tenant's row — which is also the fair-scheduling unit, unlike a global counter that would convoy every tenant behind one row.
  4. State the cost you just took on: a counter is a second source of truth that can drift, so every path that changes status must adjust it inside the same transaction, and a periodic reconciliation has to exist, with resource_revision as the authority for what the count should have been.

Follow-up

  • A resource moves from archived back to active. Which statements change, and what breaks if the counter update and the status change land in different transactions?
  • The cap becomes plan-dependent and a plan can change mid-month. Where does the number 50 live, and who reads it?

Find version gaps and relay lag with window functions

Medium · window functions · event tables · frame semantics

outbox_event holds event_id, aggregate_type, aggregate_id, aggregate_version, event_type, payload, status ('pending','published','dead'), attempts, created_at, published_at. A projection is missing rows and you must decide whether the relay skipped events or the consumer dropped them. Write three queries over the last seven days: one listing every aggregate_id whose published aggregate_version sequence has a hole, one giving per-day counts with a running total, and one returning the newest published event per aggregate. For each, say where the window function is evaluated relative to WHERE and LIMIT. PostgreSQL 16.

Approach

  1. Gaps: compute lead(aggregate_version) OVER (PARTITION BY aggregate_id ORDER BY aggregate_version) in a subquery, then filter next_version <> aggregate_version + 1 in the outer query. Window functions are evaluated after WHERE, GROUP BY and HAVING and before the outer ORDER BY and LIMIT, so the predicate cannot sit in the same WHERE clause and PostgreSQL 16 has no QUALIFY.
  2. Say what the seven-day filter does to the answer: it truncates every partition, so the first row per aggregate has no predecessor inside the window and a hole spanning the boundary is invisible. Widen the window, or join to resource.version as the authority for the true maximum.
  3. Running total: SELECT date_trunc('day', created_at) AS d, count() AS n, sum(count()) OVER (ORDER BY date_trunc('day', created_at) ROWS UNBOUNDED PRECEDING). An aggregate inside a window call is legal because grouping runs before windowing. The grouping key is unique per row here so ROWS and RANGE agree, but write the frame anyway — over ungrouped rows with tied timestamps the default RANGE frame pulls in every peer row and the total jumps.
  4. Newest per aggregate: DISTINCT ON (aggregate_id) ... ORDER BY aggregate_id, aggregate_version DESC is the cheap PostgreSQL-only form when an index matches that order; row_number() OVER (PARTITION BY aggregate_id ORDER BY aggregate_version DESC) = 1 is the portable form and needs a subquery for the same evaluation-order reason as the gap query.

Follow-up

  • Relay failover redelivers events. Does a duplicate break the gap query, and how would you detect one from this table alone?
  • Turn the gap check into a continuous monitor rather than a query someone runs after an incident. What does it watch?

What are the primary differences between HTTP/2 and HTTP/3, and how do they impact API performance?

Medium · Networking & Systems

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?

How would you design a system to monitor network latency across geographically distributed data centers?

Medium · Networking & Systems

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?

Implement a rate-limiter for an API gateway that handles millions of requests per day.

Medium · Coding & Problem Solving

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?

How would you design a scalable system to ingest and process terabytes of image data daily?

Medium · Scenario-Based & System Design

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?

Design a fault-tolerant service that handles real-time telemetry data from multiple remote sources.

Medium · Scenario-Based & System Design

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 the need for rapid feature delivery with maintaining high code quality and architectural in

Medium · Behavioral & Cultural Fit

How do you balance the need for rapid feature delivery with maintaining high code quality and architectural integrity?

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?

Explain how TCP/IP handshaking works and how you would troubleshoot packet loss in a high-throughput data pipe

Medium · Networking & Systems

Explain how TCP/IP handshaking works and how you would troubleshoot packet loss in a high-throughput data pipeline.

Approach

  1. Establish what changed and when, before forming any theory.
  2. Pick a bisection that eliminates candidates whichever way it turns out.
  3. Check the instrumentation before believing the symptom.
  4. 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?

If a critical deployment fails in a production environment, walk us through your debugging and rollback strate

Medium · Scenario-Based & System Design

If a critical deployment fails in a production environment, walk us through your debugging and rollback strategy.

Approach

  1. Establish what changed and when, before forming any theory.
  2. Pick a bisection that eliminates candidates whichever way it turns out.
  3. Check the instrumentation before believing the symptom.
  4. 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?

Suggested practice checklist

Built from the rounds and topics Planet candidates report.

Day 1 — Map the Planet loop

  • Write out the reported sequence: HR Phone Screening, Technical Evaluation, Live Coding Interview, Hiring Manager Meeting, Final HR Round.
  • 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.

Day 2 — Work Technical Interviewing

  • Spend the session on Technical Interviewing, which Planet 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.

Day 3 — Work Coding (Live/Real-Time Coding)

  • Spend the session on Coding (Live/Real-Time Coding), which Planet candidates report being tested on.
  • Write one worked example in Coding (Live/Real-Time Coding) and time yourself on it.

Deliverable: One timed worked example in Coding (Live/Real-Time Coding).

Day 4 — Work Networking Knowledge

  • Spend the session on Networking Knowledge, which Planet candidates report being tested on.
  • Write one worked example in Networking Knowledge and time yourself on it.

Deliverable: One timed worked example in Networking Knowledge.

Day 5 — Answer out loud: Networking & Systems

  • Answer aloud, timed: Explain how TCP/IP handshaking works and how you would troubleshoot packet loss in a high-throughput data pipeline.
  • Answer aloud, timed: What are the primary differences between HTTP/2 and HTTP/3, and how do they impact API performance?

Deliverable: Spoken answers to 2 reported Networking & Systems question(s), under time.

Day 6 — Answer out loud: Coding & Problem Solving

  • Answer aloud, timed: Write a function to detect cycles in a directed graph, and explain its time and space complexity.
  • Answer aloud, timed: How would you parse and process a continuous stream of coordinate data from a satellite without exhausting system memory?

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

Day 7 — Answer out loud: Scenario-Based & System Design

  • Answer aloud, timed: Describe a time when you identified a bottleneck in a software delivery process. How did you improve it?
  • Answer aloud, timed: How would you design a scalable system to ingest and process terabytes of image data daily?

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

Behavioural preparation

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

Describe your experience with networking protocols and how they relate to distributing large media files or vi

Medium · Networking & Systems

Describe your experience with networking protocols and how they relate to distributing large media files or video streams.

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 time when you identified a bottleneck in a software delivery process. How did you improve it?

Medium · Scenario-Based & System Design

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 work with a team across different time zones or language barriers. How did you

Medium · Behavioral & Cultural Fit

Tell me about a time you had to work with a team across different time zones or language barriers. How did you ensure effective communication?

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 you owned from start to finish. What did you learn, and what would you do diffe

Medium · Behavioral & Cultural Fit

Describe a challenging project you owned from start to finish. What did you learn, and what would you do differently?

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 disagreed with a technical decision made by a peer or manager. How did you resolve it

Medium · Behavioral & Cultural Fit

Tell me about a time you disagreed with a technical decision made by a peer or manager. How did you resolve it?

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?