The Palantir Coding Interview

It helps to know going in that Palantir is neither a pure LeetCode shop nor a whiteboard-algorithm gauntlet. The coding surface has two personalities. The first is a conventional but practically-flavored data-structures-and-algorithms layer: medium to medium-hard arrays and hashing, graphs and grids, trees, intervals, heaps, some dynamic programming, and a fair amount of data-structure design. The second is a set of engineering-judgment tasks most screens do not have, including a data-wrangling layer that asks you to write SQL and loop over a paginated API. Picture the production engineer who can make sense of messy data, not the competitive programmer.

The algorithm difficulty itself sits at medium, with a few problems reaching into medium-hard. What makes candidates call this one of the harder loops in tech is the framing. Prompts arrive as short stories: a spaceship approaching planets, or a delivery driver choosing which orders to pick. The first real task is pulling the actual specification out of the narrative, before you write a line of code. Every live round runs in a shared editor where the code executes against cases. A solution that looks right on the screen but misses the empty input or the boundary gets caught in front of you.

The Palantir angle

The prompt is deliberately vague, and reading requirements out of the story is graded before any code is. A Palantir problem rarely hands you a clean signature and a return type. It hands you a scenario. You are expected to ask what the inputs really are and which edge cases matter, pin down what counts as a valid answer, then restate the spec you have settled on. Candidates who dive straight into typing get dinged even when the code works, because gathering requirements from ambiguity is one of the signals the round exists to measure. Treat the first few minutes as clarifying questions, not lost time.

How the Rounds Run

The technical process opens with an online assessment on HackerRank, then a live technical phone screen, then a virtual onsite of back-to-back rounds. The assessment is the distinctive first gate. Its most-reported shape is three parts inside roughly ninety minutes. You get an algorithm or implementation problem, a SQL query built on joins and aggregation, then a REST-API task where you page through an endpoint and parse the JSON. Some loops report a coding-only variant instead, so treat the three-part version as the common case rather than a guarantee. Palantir publishes little about its process and the specific live problems rotate, so prep the shapes.

• Platform: HackerRank, then live editor. The online assessment runs on HackerRank against hidden tests, so inefficient solutions time out. Live rounds run in a shared collaborative editor over video where the code executes. This is not a whiteboard shop.
• The OA: 3 parts, ~90 min. The common shape: one algorithm problem, one SQL query on joins and aggregation, and one paginated REST-API task. Some loops report a coding-only version. The data-wrangling half is where many candidates lose the gate.
• Live screen: ~45 to 60 min, one problem. A single medium-to-hard problem in a real editor, usually with a follow-up twist added once you clear the base. Your thought process, trade-offs, edge cases, and communication are weighted as much as the final answer.
• Language: Your choice, Python common. Palantir is language-agnostic. Python is a practical default for the assessment because JSON, HTTP, and concise logic keep the API and SQL-adjacent parts fast. C++, Java, and JavaScript are all accepted.

The Palantir angle

Narrating your reasoning out loud is a first-class signal in every round, and going quiet is the most-cited reason strong candidates fail. The interviewers say plainly that they cannot read your mind, so talking through your approach carries real weight, including the trade-off you are weighing and the edge case you are choosing to handle. When a follow-up twist lands mid-round, restate it before you code so a wrong assumption gets corrected early. The pattern in rejections is consistent: the candidate who solves the problem in silence scores below the one who solves a bit less but keeps the interviewer inside their thinking the whole way.

What Comes Up

The algorithm families cluster in a stable way. Arrays and hashing lead by a clear margin across both the assessment and the live rounds, usually with a hash-map aggregation at the core and a real-world story wrapped around it. The single most-repeated problem is a portfolio-holdings aggregation, where dated per-company share events roll up into a total for each day. After that sits the practical data layer, then graphs and grids, then intervals and greedy construction, then design, with trees and dynamic programming rounding out the tail. The percentages below are relative editorial weightings drawn from what candidate reports emphasize, not measured rates, so read them as where to spend your first hours.

A few problems recur enough to name. The portfolio-holdings roll-up anchors the arrays family. It pairs naturally with a non-zero-balance accounts problem that nets transactions and returns the accounts that do not settle to zero. Intervals show up as a spaceship whose planets each cover a segment of a line, where you merge the covered ranges and emit the free gaps. Graphs arrive as a maze with several treasures to reach in the fewest steps, or a social graph asked to recommend by shared connections. Design surfaces as a least-recently-used cache with constant-time operations, or a small in-memory database that has to support transaction rollback.

The Palantir angle

The practical data layer is where the Forward Deployed flavor lives, and it is the part most candidates neglect and lose the gate on. The SQL problem is a genuine three-table join with grouping and ordering, for example total session duration per city or a month-over-month change in ratings. The API problem hands you a paginated endpoint. You loop every page, watch the total-pages boundary, parse the JSON, and aggregate the result. One reported version returns the university with the most international students across two cities, falling back to the second city when the first has none. This is the day job of a deployed engineer wrangling a customer's real feed, so it is tested directly.

SWE and FDSE Draw From One Menu

Palantir runs two engineering archetypes. In its own words, a Dev, meaning a Software Engineer, builds the platforms for many customers. A Delta, meaning a Forward Deployed Software Engineer, deploys those platforms embedded with a single customer on their messy data. Both tracks draw from the same interview menu, so the preparation overlaps heavily. The emphasis shifts. The SWE loop leans a little more conventional-algorithmic in the live coding round, reaching more often into trees and graphs, dynamic programming, design. The FDSE loop weights the practical data-wrangling parts more, since SQL and paginated feeds are closer to the actual work. It also leans harder on the open-ended decomposition work covered later in this guide. Confirm which track your loop is calibrated for. That one answer changes where to spend the last of your prep.

What This Section Covers

The lessons ahead work through the algorithm families, starting with the highest-frequency one at the top of the chart. Each one opens with how Palantir frames the pattern and the real problems that carry it. Then it hands you the most-asked versions as runnable exercises, with worked solutions and the follow-up twists stacked the way the round stacks them. The deep algorithm walkthrough for each base technique lives in the free Foundations DS&A course, and every lesson links out to it, so these pages stay on what is specifically Palantir.

Three rounds get their own dedicated lessons. A normal algorithm grind never prepares them. First comes the HackerRank online assessment that gates the loop. Then the Decomposition round where you structure a vague prompt, and the Learning and Re-engineering round where you debug unfamiliar code live. Start with the assessment, since it comes first and is where many candidates lose the gate.