Description

You will design, develop, and maintain high-performance, product-centric data pipelines.

Responsibilities

• Architect and optimize the massive-scale data warehouse and lakehouse using Snowflake.
• Lead the integration of structured and unstructured data sources into the data ecosystem.
• Implement Model Context Protocol (MCP) or similar architectures to feed data into LLM-powered products.
• Define, monitor, and enforce data quality SLAs across all pipelines.
• Mentor junior engineers and participate in enterprise-wide data infrastructure strategy.

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 for advanced data modeling and transformations.
• Deep knowledge of Snowflake data warehouse design and optimization.
• Experience implementing MCP or similar architectures for LLM systems.
• Understanding of data architecture concepts: ETL/ELT, Data Mesh, and event-driven architectures like Kafka.
• Proficiency with cloud platforms (GCP and/or AWS).

Key Skills

Education

Any Graduate