Description

Key Responsibilities

• Develop and manage Apache Airflow DAGs, schedules, and monitoring for reliable data processing
• Design AI-ready data architectures supporting ML, GenAI, RAG, vector databases, and Agentic AI
• Leverage AI-assisted development tools such as Microsoft Copilot, Claude, and Cursor to improve productivity
• Collaborate with AI/ML teams to define data ingestion, transformation, and governance patterns
• Support Agile delivery — sprint planning, backlog refinement, dependency tracking
• Mentor team members on modern data engineering and AI-assisted development practices
• Create and maintain technical documentation, data flow diagrams, and operational runbooks

Required Skills

• Strong hands-on experience with Snowflake — SQL, performance tuning, data modeling, stored procedures
• ETL/ELT pipeline design using Nexla and modern data integration tools
• Apache Airflow — DAG development, scheduling, monitoring, and troubleshooting
• Proficiency in SQL and Python at enterprise scale
• Practical experience with AI development platforms: Microsoft Copilot, Claude, GitHub Copilot, or Cursor
• Understanding of LLMs, RAG, vector embeddings, prompt engineering, and Agentic AI patterns
• Data governance, security, lineage, and compliance knowledge
• Agile delivery experience in distributed/offshore team environments

Preferred Skills

• Snowflake on Azure and Azure data services
• Azure OpenAI, Microsoft Fabric, Databricks, Amazon Bedrock, Anthropic Claude, OpenAI
• RAG implementation, semantic search, AI agents — LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel
• Azure Data Factory, Talend, or Python-based ETL frameworks
• DevOps, CI/CD, Infrastructure-as-Code, MLOps practices
• Jira, Azure DevOps, GitHub
• Insurance, insurtech, healthcare, or financial services industry experience
• Snowflake, Azure, or Generative AI certifications

Key Skills

Education

Bachelor's degree