We are looking for a Senior Data Engineer with exposure to Agentic AI concepts who can bridge modern data platforms with intelligent automation. The ideal candidate will have strong hands-on experience in AWS-based data engineering and working knowledge of emerging frameworks like LangGraph and Agentic AI use cases, especially around code generation and workflow automation.

Key Responsibilities

Data Engineering:

• Design and build scalable data pipelines using AWS Glue and PySpark
• Implement data lake architectures leveraging AWS Lake Formation
• Develop and optimize data models and transformations in Snowflake
• Ensure data quality, governance, and performance optimization across pipelines
• Work with structured and semi-structured data at scale
• Contribute to Agentic AI use cases, especially:
  • Automated code generation (ETL / SQL / PySpark)
  • Intelligent pipeline orchestration
• Work with agent orchestration frameworks like LangGraph (intermediate level)
• Understand and experiment with AgentCore or similar agent execution environments
• Collaborate with AI/ML teams to integrate LLM-driven workflows into data platforms
• Build proof-of-concepts (POCs) for AI-assisted data engineering

Required Skills

• Strong experience in:
  • AWS Glue
  • AWS Lake Formation
  • PySpark (hands-on coding)
  • Snowflake (data warehousing & performance tuning)
• Good understanding of:
  • Data lake & lakehouse architectures
  • ETL/ELT design patterns
  • Data governance and security
• Experience or exposure to:
  • Agentic AI use cases (preferably code generation / automation)
• Working knowledge of:
  • LangGraph (Intermediate)
• Basic understanding of:
  • AgentCore or similar frameworks

Good to Have

• Experience with LLM integrations (OpenAI, Bedrock, etc.)
• Understanding of prompt engineering & workflow chaining
• Exposure to MLOps / LLMOps concepts
• Knowledge of vector databases / RAG pipelines