Snowflake Developer

Role: Senior Snowflake Engineer

A Senior Snowflake Developer with Cortex experience is responsible for designing,

building, and optimizing data solutions on the Snowflake platform, with a specific

focus on leveraging Snowflake Cortex for AI-driven features like RAG (Retrieval-

Augmented Generation), LLM functions, and vector search. Key responsibilities

include developing scalable ETL/ELT pipelines, creating data models, implementing

AI assistants, and coaching other team members, all while adhering to best practices

in performance, cost control, and security. 

Skills:

• Bachelors degree in Computer Science, Software Engineering, Information

Technology, or related field required.

• At least 4 years of experience in data development and solutions in highly

complex data environments with large data volumes.

• At least 3 years of SQL / PLSQL experience with the ability to write ad-hoc

and complex queries to perform data analysis.

• At least 3-5 years of experience developing data pipelines and data

warehousing solutions using Python and libraries such as Pandas, NumPy

etc.

• Familiarity with Snowflakes architecture, including virtual warehouses, data

storage layers, and compute scaling.

Key Responsibilities:

• Design, build, and deploy data solutions using Snowflake, Snowflake Cortex

(including Cortex Analyst, LLM functions, and vector search), and Snowpark

(Python). 

• Develop AI solutions to automate tasks, provide insights, and build AI-

powered assistants or chatbots. 

• Create and maintain high-quality, scalable ELT/ETL pipelines with strong

SLAs, cost controls, and monitoring. 

• Design and implement Snowflake data models and schemas to support

complex analytical workloads. 

• Write clean, efficient Python and SQL code, conduct code reviews, and

mentor junior developers. 

• Optimize existing data pipelines and queries for performance and cost-

efficiency. 

• Implement and maintain CI/CD pipelines for automated testing and

deployment of data solutions. 

• Work with cross-functional teams, including data analysts and product

owners, to gather requirements and deliver data-driven value. 

• Apply and enforce data governance and security best practices, including

role-based access control (RBAC), masking, and row/column-level security.