Foundry Data Engineer – Build AI Pipelines

Unit8; Lausanne; On-site; CHF 120,000 - 180,000; Full time

Benefits offered by this job

Mentorship program

Self-development time

Profit sharing

Extended parental leave

Cross-office events

Fun fund

Job summary

Unit8 in Lausanne seeks an experienced Palantir Foundry Engineer to design, build, and maintain data solutions for leading clients in Europe. You will work in multi-disciplinary teams on cutting-edge data and AI projects using the Foundry platform.

You will combine Python and PySpark skills with an in-depth Foundry knowledge, ensure data quality, and collaborate with ML experts and business stakeholders. Occasional travel up to 10% is expected; a passion for solving real-world problems is

Qualifications

• 1 year minimum experience with the Foundry platform, ideally within a larger company.
• Strong client-facing skills: comfortable presenting to business and technical audiences.
• Willingness to travel up to 10% of time.
• Proficiency in Python and PySpark.
• Knowledge of data modeling and basic data science concepts.

Responsibilities

• Design, build, and maintain robust data pipelines and processing systems using Palantir Foundry.
• Drive optimization, testing, and tooling to ensure high data quality.
• Collaborate with software engineers, ML experts, and stakeholders in cross-functional teams.
• Work in multi-functional agile teams to deliver on product objectives.

Skills

Palantir Foundry

Python

PySpark

Data modeling

Data science concepts

Client-facing skills

Security concepts in Foundry

Travel up to 10%

Tools

AIP

Workshop

Code repository

Pipeline Builder

Ontology

Data connection

Job description

Unit8 in Lausanne seeks an experienced Palantir Foundry Engineer to design, build, and maintain data solutions for leading clients in Europe. You will work in multi-disciplinary teams on cutting-edge data and AI projects using the Foundry platform.

You will combine Python and PySpark skills with an in-depth Foundry knowledge, ensure data quality, and collaborate with ML experts and business stakeholders. Occasional travel up to 10% is expected; a passion for solving real-world problems is