Snowflake Data Engineer
6 days ago
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 Snowflake's 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,
-
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