Senior Data Engineer, Snowflake

• The ideal candidate brings a solid background in data engineering, with deep expertise in Snowflake and cloud technologies
• 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

Desirable

• We are looking for a skilled Snowflake Data Engineer to join our Product and Data Science team
• In this role, you will design, build, and maintain robust data pipelines, ensuring our data infrastructure is scalable, reliable, and efficient
• You will partner closely with product and data science engineers, providing tools, automation, and best practices to accelerate their work, improve data quality, and ensure consistency across pipelines and dashboards
• Additionally, you will play a critical role in cost optimization for data operations, owning efficient data modeling and pipeline performance
• This position is also key in building and scaling our enterprise data warehouse, helping to shape the future of our data ecosystem
• 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