Description

You will architect and optimize Snowflake data platforms on AWS, ensuring high performance and cost efficiency. You own the end-to-end ELT/ETL pipelines using Snowflake, AWS services, and modern data engineering tools. You implement advanced Snowflake features including performance optimization, warehousing strategy, data sharing, streams & tasks, time travel, and zero copy cloning.

Responsibilities

• Design data foundations supporting Agentic AI and GenAI workloads, including AI-ready datasets, vectorized data, and metadata-driven pipelines.
• Collaborate with AI/ML teams to enable autonomous agents, LLM-driven analytics, and intelligent data orchestration.
• Provide technical leadership, code reviews, and mentoring to data engineering teams.
• Partner with business and product stakeholders to translate analytics and AI requirements into scalable data solutions.

Required Skills

• 8-10 years of experience in Big Data Engineering or Analytics.
• Expert-level Snowflake experience, including large-scale production deployments.
• Strong hands-on experience with AWS: S3, EC2, Lambda, Glue, Redshift/Athena, IAM, CloudWatch, Step Functions.
• Proven experience building cloud-native data architectures on AWS.
• Solid programming skills in Python and SQL.
• Experience with data modeling for analytics and AI use cases.
• Hands-on or applied exposure to Agentic AI, Generative AI, or AI-driven data platforms.
• Experience leading or mentoring engineering teams in enterprise environments.

Key Skills

Education

Any Gradute