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