Description

Design and implement large-scale distributed data processing workflows and production-ready data services.

This role is on-site.

Responsibilities

• Build and maintain data pipelines and models using PySpark for analytics and downstream consumption.
• Develop data engineering solutions within Palantir environments, ensuring correctness and performance.
• Apply system architecture and design patterns to create maintainable, scalable components.
• Collaborate with engineering and product teams to translate requirements into production-ready data services.

Required Skills

• 5-10 years of experience in data engineering and distributed systems.
• Proficiency in PySpark for distributed data processing and pipeline development.
• Hands-on experience building and delivering data solutions in Palantir environments.
• Strong understanding of system architecture and design patterns for scalable distributed software.
• Experience with production engineering practices for reliable, maintainable data workflows.
• Degree in Computer Science, Engineering, or a related field (or equivalent practical experience).

Preferred Skills

• Experience delivering end-to-end data engineering solutions as a Data Engineer.

Key Skills

Education

Any Graduate