Description

Design and implement scalable data architectures and processing pipelines using Python, PySpark, and Palantir.

Responsibilities

• Design and develop efficient data architectures leveraging Python, PySpark, and Palantir.
• Oversee the implementation of data integration and processing pipelines to ensure seamless operation.
• Ensure data quality and integrity through rigorous validation and continuous monitoring processes.
• Optimize data storage and retrieval mechanisms to improve overall system performance.
• Provide technical guidance and mentorship to junior team members while conducting code reviews.

Required Skills

• 10+ years of experience in data architecture roles.
• Expert-level proficiency in Python.
• Hands-on experience with Palantir platform implementation.
• Proficiency with PySpark for distributed data processing.
• Proven track record of designing scalable data architectures.
• Ability to translate business requirements into technical solutions.
• Strong troubleshooting skills for complex data processing issues.
• Any Graduate degree.

Key Skills

Education

Any Graduate