How to Use This Question Bank + Self-Assessment

Palantir Forward Deployed Software Engineer (FDSE) interviews tend to test a mix of coding, data work, and real world problem framing, not just algorithms.
This course is a question bank for last mile practice, meaning we train you to produce real interview answers under time pressure, then score them and fix the common mistakes.

The core rule is that we practice without AI tools, because the goal is to build your own speed, structure, and confidence.
We also never treat this as an official Palantir guide, and anywhere the process details can vary we label them as commonly reported rather than guaranteed.

Practice Like It Is Live
If you use AI during practice, you remove the exact skill the interview is trying to measure.

A second rule is that your stories must be your real experiences, and school projects count.
When you mention results, label them as measured, estimated, or anecdotal, and never invent numbers to sound impressive.

Finally, we do not copy reported interview questions word for word, because the point is to train the underlying skill, not memorize a leaked prompt.
Each lesson gives 5 to 6 original questions for one round, with a model answer, a Scoring line for what the interviewer is judging, and a Common mistake line that names the trap.

Let’s check what must be labeled as commonly reported, and what not to assume about the online assessment:

Palantir context you need for answers

Palantir builds platforms like Foundry, which is used to integrate data and run operations for many customers, and Gotham, which is used mainly in government and defense settings.
You do not need deep product trivia, but you do need a clean one sentence explanation so you sound grounded when you answer “why Palantir” and when you frame systems questions.

Palantir also commonly describes two engineering tracks, Dev and Delta, that change what your loop emphasizes.
A Dev is a software engineer building the platforms themselves, and a Delta is an FDSE who embeds with one customer to deploy those platforms on messy real data.

Track details can also differ between US Government and Commercial postings, especially around clearance and travel, so we do not generalize one to the other.
The safest move is to confirm your track and constraints from your own recruiter or invitation, then practice the same menu of skills.

Here is a simple comparison we will use when we pick which questions to drill first:

The commonly reported loop we will practice

Palantir does not publish a fixed FDSE interview process, so everything about round names and order is commonly reported and can vary by team, location, and level.
What stays consistent is the skill mix, and this question bank is built around that mix.

A commonly reported early gate is an online assessment, often 60 to 90 minutes on HackerRank, with about three tasks.
Those tasks are commonly an implementation problem, a SQL query, and a paginated REST API task, meaning you must loop through pages of results from an endpoint and aggregate what you find.

Then a commonly reported onsite or panel pulls from a pool of round types such as decomposition, learning, re-engineering, coding, and system design.
Behavioral questions are often embedded inside those technical rounds rather than appearing as one separate behavioral interview.

This course breaks that pool into nine round skills we can rate and improve, including recruiter screen, the three online assessment parts, decomposition, learning, re-engineering, system design, and behavioral.
To keep our prep honest, we score each skill separately instead of saying “I am good at interviews” as one bucket.

Let’s look at the nine rounds we will use for the self assessment and practice plan: