Description

You will design and maintain high-performance data pipelines and warehouse architectures.

This role is hybrid.

Responsibilities

• Architect and optimize the data warehouse and lakehouse using Snowflake.
• Implement Model Context Protocol (MCP) to feed contextual data into LLM-powered products.
• Integrate structured and unstructured data sources into the data ecosystem.
• Define and enforce data quality SLAs across all pipelines.
• Mentor junior engineers on code quality and data architecture best practices.

Required Skills

• 8+ years of progressive experience in data engineering with demonstrated leadership.
• Expert-level SQL for building performant, scalable queries on massive datasets.
• Strong Python programming skills focused on distributed computing and data manipulation.
• Production-level experience with large-scale batch and streaming data processing.
• Hands-on experience with DBT (Data Build Tool) for advanced data modeling.
• Deep knowledge of Snowflake data warehouse design and optimization.
• Proficiency with cloud platforms (GCP and/or AWS) and Terraform.
• Strong understanding of ETL/ELT and Data Mesh concepts.

Preferred Skills

• Experience implementing MCP or similar architectures for LLM systems.
• Proficiency with Kafka for streaming data.

Key Skills

Education

Any Graduate