Senior Data Engineer - Product

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. We are looking for a skilled Snowflake Data Engineer to join our Product and Data Science team. The ideal candidate brings a solid background in data engineering, with deep expertise in Snowflake and cloud technologies. 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 scientists, 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. Responsibilities - 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. Qualifications - 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. - Proven experience working with Spark for large-scale data processing. - 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. Preferred Qualifications: - 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). Every Snowflake employee is expected to follow the company’s confidentiality and security standards for handling sensitive data. Snowflake employees must abide by the company’s data security plan as an essential part of their duties. It is every employee's duty to keep customer information secure and confidential. Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake. How do