Description

You will build and maintain data products focused on GenAI and Lakehouse architectures.

Responsibilities

• Build new data products using Python and PySpark.
• Aggregate data and perform daily pulls to analyze trends.
• Develop RAG (Retrieval-Augmented Generation) architectures to provide context for LLM applications.
• Use Databricks and Spark to run reports and optimize metadata within data lakes.

Required Skills

• 5+ years of experience in data engineering.
• Proficiency in Python.
• Hands-on experience with PySpark.
• Experience working within AWS environments.
• Expertise using Databricks and Lakehouse architectures.
• Strong SQL skills for data manipulation and testing.
• Understanding of RAG (Retrieval-Augmented Generation) implementation.

Preferred Skills

• Degree in any field (Any Graduate).

Key Skills

Education

Any Graduate