Lead Data Engineer :: Hybrid :: W2 Position

Role: Lead Data Engineer – Snowflake / GenAI
Position Overview
We are looking for Lead Data Engineer to join our Technology and Data Engineering team. The ideal candidates will have strong hands-on experience building and supporting enterprise data platforms, ETL/ELT pipelines, and Snowflake solutions, along with exposure to modern AI/GenAI technologies.
You will work closely with Data Engineering, Product Engineering, AI/ML, Architecture, and business teams to build scalable, reliable, and AI-ready data solutions.
Key Responsibilities

• Design, develop, and maintain scalable data engineering solutions and pipelines.
• Build and support ETL/ELT pipelines using Snowflake, Python, SQL, Airflow, Nexla, or similar technologies.
• Develop and optimize enterprise Snowflake data platforms.
• Build data solutions that support analytics, AI, and machine learning initiatives.
• Support GenAI, LLM, RAG, vector database, semantic search, and AI-agent use cases.
• Perform data pipeline monitoring, troubleshooting, performance tuning, and production support.
• Implement data quality, governance, security, privacy, and data lineage practices.
• Collaborate with Product Engineering, AI/ML, Architecture, and business stakeholders.
• Participate in Agile/Scrum ceremonies, sprint planning, stand-ups, and technical discussions.
• Create and maintain technical documentation and solution designs.
• Coordinate with onsite, offshore, and cross-functional engineering teams.
• Troubleshoot complex data and production issues and drive them through resolution.

Required Skills

• Strong hands-on experience with Snowflake.
• Strong SQL and Python development skills.
• Experience developing ETL/ELT pipelines.
• Experience with Apache Airflow or similar workflow orchestration tools.
• Experience with Nexla or similar data integration/ETL platforms.
• Experience building enterprise-scale data platforms and pipelines.
• Understanding of data governance, data security, privacy, and data lineage.
• Experience supporting analytics, AI, or machine-learning data platforms.
• Hands-on or practical experience with AI/GenAI technologies.
• Understanding of LLMs, RAG, vector databases, semantic search, and Agentic AI.
• Strong troubleshooting, problem-solving, communication, and stakeholder-management skills.
• Experience working in Agile/Scrum environments.

Preferred Skills

• Experience with Azure and Snowflake on Azure.
• Experience with Azure OpenAI, Microsoft Fabric, Databricks, Amazon Bedrock, or similar platforms.
• Experience with RAG, semantic search, vector databases, and AI agents.
• Exposure to LangChain, LangGraph, CrewAI, AutoGen, or Semantic Kernel.
• Experience with DevOps, CI/CD, Infrastructure as Code (IaC), or MLOps.
• Experience in insurance, insurtech, healthcare, or financial services environments.