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Big Tech & Enterprise Software

Palantir

Data analytics / government / enterprise · Data Engineering interview

The data role is Forward Deployed Software Engineer: practical coding, decomposition/debugging, data architecture, and a hard mission filter.

Cloud / platform

Foundry on AWS/Azure/on-prem; Spark, Python, TypeScript

Reported difficulty

~3.4 / 5 · ~59% positive

PythonSQLData pipeliningData architecture

Hiring process

Recruiter (mission filter)

Online Assessment

Onsite (4 of: decomp, re-eng, coding, learning, design)

Hiring Manager

Offer

Round-by-round breakdown

Online Assessment

Medium confidence

HackerRank 60–90 min: coding + SQL + sometimes API integration
Implementation-heavy mini-projects

Coding

· CodePair + embedded behavioralMedium confidence

DS&algo medium–hard (DP, graphs, trees, arrays, hash tables)
Practical motivations over abstract puzzles

Decomposition / Design

Medium confidence

Design a chess game from scratch (pieces, board, rules, state)
Build a parking-garage management system

Re-engineering / Debugging

Medium confidence

Given ~500–1000 lines, told how it should work; find & fix bugs

System & pipeline design prompts

Data architecture for a client problem (FDSE emphasis: pipelining + client outcomes)

Prep — high priority

Practical coding (DP/graphs/trees/hashing)
Decomposition design (chess/parking-style)
Debugging long codebases; Python+SQL data pipelining
Articulate mission alignment

Prep — medium priority

Data architecture for client problems
Behavioral/social competence

Rejection patterns

Weak mission/culture alignment (filtered early)
Abstract over practical coding
Cannot debug long real code
Low social competence (FDSE is client-facing)

Reported experiences

FDSE (Denver)

Accepted offer (positive)First-hand

JoinTaro (Mar 2025): recruiter → OA → onsite (coding/decomposition/debug/architecture) → HM.

FDSE (US)

No offer (negative)First-hand

JoinTaro (Nov 2025): same loop; useful for failure modes (mission fit + practical coding).

Rehearse for Palantir

Answered questions on what Palantir actually asks — each with the short answer, the answer that gets you rejected, and the follow-up.

Then build one and have it reviewed: design a daily orders pipeline or model a marketplace. No account.

All interview experiences

Openingloading the content…

Big Tech & Enterprise Software

Palantir

Data analytics / government / enterprise · Data Engineering interview

The data role is Forward Deployed Software Engineer: practical coding, decomposition/debugging, data architecture, and a hard mission filter.

Cloud / platform

Foundry on AWS/Azure/on-prem; Spark, Python, TypeScript

Reported difficulty

~3.4 / 5 · ~59% positive

PythonSQLData pipeliningData architecture

Hiring process

Recruiter (mission filter)

Online Assessment

Onsite (4 of: decomp, re-eng, coding, learning, design)

Hiring Manager

Offer

Round-by-round breakdown

Online Assessment

Medium confidence

HackerRank 60–90 min: coding + SQL + sometimes API integration
Implementation-heavy mini-projects

Coding

· CodePair + embedded behavioralMedium confidence

DS&algo medium–hard (DP, graphs, trees, arrays, hash tables)
Practical motivations over abstract puzzles

Decomposition / Design

Medium confidence

Design a chess game from scratch (pieces, board, rules, state)
Build a parking-garage management system

Re-engineering / Debugging

Medium confidence

Given ~500–1000 lines, told how it should work; find & fix bugs

System & pipeline design prompts

Data architecture for a client problem (FDSE emphasis: pipelining + client outcomes)

Prep — high priority

Practical coding (DP/graphs/trees/hashing)
Decomposition design (chess/parking-style)
Debugging long codebases; Python+SQL data pipelining
Articulate mission alignment

Prep — medium priority

Data architecture for client problems
Behavioral/social competence

Rejection patterns

Weak mission/culture alignment (filtered early)
Abstract over practical coding
Cannot debug long real code
Low social competence (FDSE is client-facing)

Reported experiences

FDSE (Denver)

Accepted offer (positive)First-hand

JoinTaro (Mar 2025): recruiter → OA → onsite (coding/decomposition/debug/architecture) → HM.

FDSE (US)

No offer (negative)First-hand

JoinTaro (Nov 2025): same loop; useful for failure modes (mission fit + practical coding).

Rehearse for Palantir

Answered questions on what Palantir actually asks — each with the short answer, the answer that gets you rejected, and the follow-up.

Then build one and have it reviewed: design a daily orders pipeline or model a marketplace. No account.

All interview experiences