8 months ago
Base Salary
$264k - $380k/yr
Responsibilities
- Design and implement highly available distributed platforms and pipelines.
- Enhance Snowflake’s overall data infrastructure, including ingestion, processing, replication, export, and data layout capabilities.
- Lead projects from idea formulation through design, implementation, and successful productionization.
- Collaborate with product managers, architects, engineering teams, data science organizations, and business groups on end-to-end solutions.
- Provide strong technical leadership to the team and partner teams.
- Enable data science, business, and engineering organizations to build comprehensive analytics quickly and effectively.
- Dive deeply into complex system design and implementation when needed.
- Follow Snowflake’s confidentiality, data security, and customer information protection standards.
Requirements
- 15+ years of experience in distributed systems, including experience in data warehouse or data infrastructure software development.
- A strong track record delivering large-scale, resilient distributed systems and services.
- Extensive development experience in cloud environments such as AWS, Azure, and GCP.
- Experience with distributed systems and databases.
- Strong hands-on software development and system design skills.
- Strong collaboration and communication skills.
- BS, MS, or PhD in Computer Science or a related major, or equivalent experience.
- Experience in machine learning is preferred.
Benefits
- Salary and benefits information for United States roles is provided on the Snowflake Careers Site.
Tech Stack
Categories
BackendData Engineering
About Snowflake
Snowflake builds a cloud-native data platform used by enterprises to store, integrate, share, and analyze data across AWS, Azure, and Google Cloud. Its core products span data warehousing, data lakes, data engineering, and governed data sharing, sold via consumption-based subscriptions. Founded in 2012 and publicly traded on the NYSE (SNOW) following a 2020 IPO, Snowflake supports analytics and data application workloads across industries.