Snowflake delivers the AI Data Cloud, a global network enabling organizations to mobilize data at near-unlimited scale and concurrency, supporting data-driven decision-making and innovation across various industries. The company's core service is a cloud-based data platform that integrates data warehousing, data lakes, and data sharing, empowering businesses to analyze and share data securely and efficiently. Snowflake's technology influences a broad range of enterprise clients seeking scalable data solutions. Its mission is to facilitate seamless data collaboration and unlock insights for competitive advantage.
💻 Software📊 Data Analytics🤝 B2B
Snowflake Data Engineer
~30 days ago
🇺🇸 United States+1📍🇵🇱 Warsaw📍🇵🇱 Warsaw
•🔀 Hybrid
•🏠 Remote
•🗄️ Backend
•⚙️ Mid-Level
•🕛 Full Time
Description
Design, develop, and maintain scalable data pipelines using Snowflake and cloud technologies.
Own and manage cost optimization for Product and Data Science team operations.
Optimize pipelines for performance, reliability, and efficiency.
Build and maintain dashboards and reporting platforms using Streamlit.
Collaborate with cross-functional teams to gather requirements and deliver robust data solutions.
Work with modern AI tools, including Cursor, to accelerate development.
Implement data governance, security best practices, and access control policies.
Develop and enforce data quality checks, SLA monitoring, and dependency tracking.
Utilize version control systems (e.g., Git) and manage deployment workflows.
Proactively troubleshoot and resolve data-related issues.
Requirements
Bachelor’s degree in Computer Science, Engineering, or a related field.
Proven hands-on experience with Snowflake, including data modeling, ETL/ELT development, and performance tuning.
Advanced proficiency in Python, with experience scripting and automating data workflows.
Demonstrated experience building Streamlit applications integrated with Snowflake.
Strong command of SQL for complex data querying and analysis.
Familiarity with cloud platforms such as AWS, Azure, or GCP, and services like S3, Redshift, or bigquery.
Strong problem-solving and communication skills.
Ability to thrive both independently and as part of a collaborative, fast-paced team environment.
Master’s degree in Computer Science, Engineering, or a related discipline.
Strong understanding of data warehousing principles, architecture, and best practices.
Experience working within Agile development frameworks (e.g., Scrum, Kanban).
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