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Data Engineer - Palantir Foundry

ETHjuniors · Zurich, Zurich, Switzerland · CHF 45/yr

Business Consulting and Services · 51-200 employees

Jun 16
Mid (2-5 yrs) Full-time Switzerland
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About the role

The role involves data engineering tasks specifically focused on the Palantir Foundry platform. You will be responsible for managing and optimizing data pipelines within this environment.

What they look for

Data Engineering Palantir Foundry

Requirements

Candidates should have experience with data engineering workflows. Proficiency in Palantir Foundry is a primary requirement for this position.

Full description

Join a leading Swiss media and technology company with a strong digital focus and help build scalable data pipelines, reliable data models, and business-ready data products within Palantir Foundry.

  • Build and scale ETL/ELT data pipelines directly in Palantir Foundry, using tools such as Code Repositories and Pipeline Builder.
  • Integrate data from various source systems and make it available for analytics, reporting, and business applications.
  • Support the modelling of data within the Foundry Ontology, making complex business logic accessible for analysts and end users.
  • Write clean and efficient code, mainly in PySpark and SQL, to clean, transform, and process large data volumes.
  • Collaborate closely with Data Scientists, Analysts, and business departments to translate requirements into functional data models in Foundry.

Requirements

  • Academic background in Computer Science, Data Engineering, Business Informatics, Mathematics, Statistics, or a related field
  • Initial experience with Palantir Foundry is a strong plus. Alternatively, a solid foundation in data processing and high motivation to learn the Palantir ecosystem in depth.
  • Fluent in English; German is an advantage
  • Good to very good knowledge of Python, ideally with experience in PySpark or Pandas
  • Strong skills in SQL
  • Good basic understanding of relational databases, data architectures, distributed systems, and Big Data challenges

Benefits

Start: September/ October 2026

Duration: 1-1.5 years (probability of extension)

Workload: 80-100%

Location: Hybrid

Salary: competitive