Overview: Data Engineer specializing in Snowflake; design, implement and maintain data architecture
Responsibilities: Data transformations and design: Collaborate with cross-functional teams to understand data requirements and design scalable data transformations using Snowflake
Snowflake implementation and maintenance: Configure and optimize Snowflake environments; implement and maintain data pipelines and ETL processes
Data modeling: Design and implement data models to support analytical needs; work with data scientists, analysts
Performance optimization: Monitor and optimize Snowflake query performance; apply storage, indexing, partitioning best practices
Data integration & automation: Integrate data from various sources into Snowflake; manage pipelines; collaborate with data source owners; develop and deploy ML models to automate processes and integrate customer data across systems; build predictive models to anticipate internal data needs
Security and compliance: Implement security measures; ensure data governance compliance
Documentation: Create and maintain documentation; provide training on Snowflake best practices
Collaboration: Work with data scientists, analysts, and IT to deliver data solutions; integrate Snowflake with other systems
Requirements
Bachelor's degree in Data or Computer Science, Information Technology, or a related field
Proven experience as a Data Engineer with a focus on Snowflake
In-depth knowledge of Snowflake architecture, features, and best practices
Proficiency in SQL
Experience with data modeling tools and AI/ML framework
Strong problem-solving skills and the ability to optimize data workflows for performance
Experience with cloud platforms (e.g., Snowflake, Azure) and related services
Familiarity with data integration tools and ETL processes
Excellent communication and collaboration skills
Certifications in Snowflake or related technologies are a plus
Strong understanding of data integration practices and API connectivity across SaaS platforms