Key Responsibilities
- Design and implement enterprise-scale data architecture and solutions.
- Build and optimize ETL/ELT pipelines using Python and SQL.
- Design enterprise data warehouses and cloud-based data platforms.
- Develop AI-ready data pipelines to support Generative AI and ML applications.
- Design and implement RAG architectures and semantic search solutions.
- Work with vector databases, LangChain, LangGraph, and AI agents.
- Integrate Azure OpenAI and AWS Bedrock into enterprise data solutions.
- Design real-time analytics and event-driven data architectures.
- Develop and manage streaming data pipelines using Apache Kafka.
- Implement Change Data Capture (CDC), Debezium, and incremental data processing.
- Design and manage batch and real-time data processing architectures.
- Work with Snowflake, Databricks, and other cloud data platforms.
- Collaborate with AI/ML engineers, data engineers, and business stakeholders.
Required Skills
- 10+ years of experience in Data Architecture / Data Engineering.
- Strong hands-on experience with ETL/ELT, Python, and SQL.
- Enterprise Data Warehousing experience.
- Treasure Data / Treasure Data CDP – Key Requirement.
- Generative AI, RAG, and Vector Databases.
- LangChain / LangGraph and AI Agents.
- Azure OpenAI / AWS Bedrock.
- Real-time analytics and event-driven architecture.
- Apache Kafka and streaming data pipelines.
- Snowflake / Databricks or equivalent cloud data platforms.
- AWS / Azure / Google Cloud Platform data engineering services.
- CDC, Debezium, and incremental data processing.
- Experience designing batch and real-time enterprise data architectures.
Rate:
Not specified
Location:
Dallas
IR35 Status:
Outside
Remote Status:
Remote
Industry:
Data & Analytics
Seniority Level:
Senior