Software Engineer, New Grad - Query Engines
Palantir Technologies
New York, NY · Posted October 19, 2026
No experience needed. The posting says: “Software Engineer, New Grad - Query Engines”
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Pay compared with the market
This listing does not state pay. Across 475 open software engineer listings that state pay, the middle half runs $159,500 to $238,500 and the median is $197,500.
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How AI is used in this kind of work
Among software developers, AI is already used for some of the tasks. Measured exposure for software developers: 29% (some).
Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.
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About the job
A World-Changing Company
Palantir builds the world’s leading software for data-driven decisions and operations. By bringing the right data to the people who need it, our platforms empower our partners to develop lifesaving drugs, forecast supply chain disruptions, locate missing children, and more.
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.