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Salary
≈ $112k – $228k per year (Estimated)
Location
Hybrid (New York, United States)
Seniority
Junior
Visa
H-1B filings in 12 months: 207 · for this role: 74 · green card filings: 38
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 21, 2026. First seen by Alion on Oct 19, 2026. Palantir Technologies scores C on the Alion truth index.

Overview
Company
Impact
Profile match
Palantir Technologies is an American software company founded in 2003 that builds platforms for integrating, analysing and acting on large and fragmented datasets. Its Gotham platform serves defence, intelligence and law enforcement customers, Foundry brings the same data-operating model to commercial industries such as manufacturing, healthcare and energy, and the Artificial Intelligence Platform layers large language models over both. Headquartered in Denver, Colorado and listed on the New York Stock Exchange since 2020, the company is known for deploying forward engineers directly inside customer organisations.

The Role

We are a software engineering team applying open-source data technologies to some of the world's hardest and most important problems. We build the data processing infrastructure that underpins Palantir Foundry, supporting applications that help hospitals care for more patients, help clinical teams coordinate timely diagnoses, and keep essential supplies moving through global disruption.

You will work deep inside the systems that make this possible: how computations are represented, how query plans are optimized, how operators execute, and how data is read and written efficiently. We build on and extend Apache Spark, Apache DataFusion, and Apache Iceberg, bringing advances in open-source engines and table formats into the demanding environments our customers operate in. Our work serves many products and workloads across Foundry, including no-code pipelines, interactive analysis, and the processing that keeps the Ontology up to date.

Working alongside experienced engineers, you will take on real problems in our production systems. That could mean writing a new planning rule, adding a capability to a native execution engine, or making large tables faster to scan. You will see your work through design, code review, testing, and release. Correctness, compatibility, and predictable performance are central to everything we build, and you will learn how to deliver all three.

Join us if you want to learn how modern data systems work from the inside and apply that knowledge to consequential problems.

Technologies We Use

  • Java, Scala, Rust, and Python
  • Apache Spark, Apache DataFusion, Apache Comet, and Velox for data processing and query execution
  • Apache Iceberg for table management and catalog interoperability
  • Apache Arrow and Apache Parquet for in-memory data processing and columnar storage
  • Gradle and Cargo for builds, and GitHub for collaboration
  • You do not need prior experience with these technologies. We expect you to learn them here.

What We Value

  • Curiosity about how data systems work, from query optimizers and execution operators to file formats and distributed processing
  • A high bar for correctness and a willingness to dig until you understand why something behaves the way it does
  • Comfort following a problem across languages, services, and layers of the stack
  • A practical approach to performance, grounded in measurement rather than intuition
  • Eagerness to learn, ask questions, and incorporate feedback
  • Interest in applying deep systems engineering to real-world problems, with empathy for the people who depend on our software

What We Require

  • Currently pursuing or recently completed a Bachelor's, Master's, or PhD in Computer Science, Mathematics, Software Engineering, Physics, or a similar field, or equivalent practical experience
  • Proficiency in at least one language such as Java, Rust, Scala, C++, or C
  • Strong foundations in algorithms, data structures, and concurrency
  • Strong written and verbal communication skills
  • Coursework or projects in databases, compilers, operating systems, or distributed systems
  • Contributions to open-source projects
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