12 Palantir Technologies Forward Deployed Engineer (New Grad) Interview Questions (2026)

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STAR. This is the core FDE skill. Pick a case where you turned 'we need better visibility' into a shippable feature. Walk through: what questions you asked, how you scoped, what you cut, how you validated with the user. Palantir FDE candidates are screened heavily for ambiguity tolerance.

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Tie to wanting customer-facing impact, learning new domains rapidly, owning end-to-end deployments rather than building infrastructure components. If you've done client work, internships, or research where you had to translate domain needs into code, mention it. Avoid 'I want to travel' — too superficial.

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STAR. FDEs constantly tell customers their requested feature isn't possible, will take longer, or solves the wrong problem. Pick a moment when you delivered hard truth with care. Show you led with empathy and options, not just 'no.'

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STAR. FDEs land in logistics, hospitals, factories, agencies — none of which you know on day one. Pick a project where you ramped on a new domain quickly: read docs, sat with users, asked dumb questions, then shipped something useful. Show humility and curiosity.

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STAR. FDEs present to executives, ops managers, analysts — rarely fellow engineers. Pick a project where you simplified a technical result for a business audience. Show you adapted vocabulary, used visuals, and led with the business outcome, not the implementation.

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Recursive: if root is null or matches either target, return root. Recurse on both children. If both children return non-null, root is the LCA. Else return whichever child is non-null. O(N) time, O(H) space.

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DFS with three node states: unvisited, in-progress, done. If you encounter an in-progress node during recursion, there's a cycle. O(V + E) time, O(V) space. Alternative: Kahn's algorithm (topological sort by indegree); if not all nodes processed, cycle exists.

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Map the existing flow first (frequency of export, schema, freshness, who consumes it today). Build a thin ingest layer that picks up new files (S3 / SFTP / file watcher), validates against schema, lands in raw zone, then transforms. Plan for schema drift and partial failures. Palantir loves the question because it's the actual day-job. Show pragmatism over elegance.

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Define slow. Is it load time, query latency, render? Get a specific reproducer. Check the obvious: query time (look at the SQL), data volume, browser network panel, server-side logs. Walk through the request layer by layer. FDE work is full of this; Palantir wants signal you can methodically diagnose.

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Multi-stage. Stage 1: exact match on canonical key (lowercase + strip whitespace + remove special chars). Stage 2: fuzzy match using a similarity metric (Levenshtein distance, soundex). Stage 3: human-in-the-loop review queue for borderline matches. Discuss false-positive/negative tradeoffs and how to tune the threshold per use case.

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Try each format in priority order. Use the language's date-parsing library. Detect ambiguity (e.g., 03/04/2026 — March 4 or April 3?) and either prefer one based on locale hint or flag for human review. Real FDE problem — Palantir wants to see pragmatism, not just regex.

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Entities: Patient, Admission, Encounter, Diagnosis, Provider. Admission has many Encounters; each Encounter has one Provider and many Diagnoses. Discuss: PHI handling (don't store unnecessary identifiers), temporal joins (which diagnosis was active at admission), and the FHIR standard as a real-world reference. Palantir's healthcare work demands this thinking.