Data Engineer; Palantir

Responsibilities

• Build Pipelines in Foundry:
  Develop and scale data pipelines (ETL/ELT) directly within Palantir Foundry (e.g., via Code Repositories, Pipeline Builder) and integrate data from a variety of source systems.
• Data Modeling & Ontology:
  Map data into the Foundry Ontology, making complex business logic tangible and accessible for analysts and end-users.
• Data Quality & Lineage:
  Implement health checks, monitor data quality across the entire data lineage process, and ensure pipelines run stably.
• Code & Transformation:
  Write clean, efficient code (primarily in PySpark and SQL) to clean and transform large volumes of data.
• Team
  
  Collaboration:
  
  Work closely with Data Scientists, Analysts, and business departments to translate their requirements into functioning data models within Foundry.

• Initial professional experience in Data Engineering:
  Junior (e.g., internships/working student roles) or Mid‑Level (approx. 1–3 years in a permanent role).
• Good to excellent knowledge of Python (ideally experience with PySpark or Pandas) and high proficiency in SQL.
• Prior experience with Foundry (e.g., Contour, Code Repositories, Ontology) is a massive plus. If not, a strong foundation in data processing and a motivation to dive deep into the Palantir ecosystem.
• Solid basic understanding of relational databases, data architectures, and the challenges of working with distributed systems (Big Data).
• Solution‑oriented, analytical thinking, and enthusiasm for working with complex datasets and learning new tools.

Start date:

September

Location:

Zurich, CH

Duration:
Permanent contract

Language:
Fluent in English;
German is a plus