Key Responsibilities
- Transform raw production data into analytics-ready formats for business insights and product development
- Design and implement efficient data schemas, data marts, and semantic layers optimized for AI-ready LLM querying
- Develop and maintain data workflows using Airflow, ensuring reliability and scalability of data pipelines
- Collaborate with data analysts and product teams to translate business needs into scalable data solutions
- Monitor data quality and integrity, optimizing models and schemas to support evolving requirements
- Build and maintain data visualization tools using platforms like Looker, Superset, or HEX
Requirements
- Strong foundation in data modeling, SQL, and schema design for performance and accessibility
- Proficiency with modern data tools including Airflow, Snowflake, and visualization platforms
- Solid Python skills for building data workflows, automations, and transformations
- Experience with large language models (LLMs), prompt engineering, or retrieval-augmented generation (RAG) is a plus
- Strong problem-solving skills, ownership, and excellent communication abilities