Description

• Must have strong hands-on ETL/ELT, Python, SQL, and Enterprise Data Warehousing experience.
• AI/Generative AI data engineering experience is strongly required— RAG, vector databases, LangChain/LangGraph, AI Agents, Azure OpenAI, AWS Bedrock, etc.
• We are specifically interested in candidates who understand how enterprise data platforms support modern AI/ML and Generative AI applications.
• Treasure Data / Treasure Data CDP experience is a key requirement — please prioritize candidates with real production experience.
• Strong experience with real-time analytics, event-driven architecture, and streaming data pipelines.
• Hands-on Apache Kafka experience is highly preferred.
• Experience with Snowflake, Databricks, or equivalent cloud data platforms.
• Strong experience with AWS, Azure, or GCP data engineering services.
• CDC or Debezium and incremental data processing experience is required.
• Candidate should have experience designing batch + real-time enterprise data architectures.
• Experience building AI-ready data pipelines / semantic search / RAG infrastructure will be a major plus.
• Please do not submit traditional ETL/BI only profiles.

Specific Ask: Please submit candidates who have Treasure Data + Real-Time Analytics + Enterprise

ETL/Data Warehouse experience, ideally combined with Kafka and Generative AI

Key Skills

Education

Bachelor's degree