Principal Software Engineer

Responsibilities

• Define and drive the technical direction for Snowflake's core data engineering and streaming transformation primitives, including Streams, Tasks, and Dynamic Tables.
• Lead multi-quarter technical investments in performance, scalability, correctness, and reliability.
• Partner with product, research, and peer engineering teams to co-design primitives that compose across the data engineering stack.
• Act as a force multiplier by running architectural reviews and setting the technical bar for design documents.
• Work with customers and field teams to understand usage patterns and prioritize future development.

Requirements

• 15+ years of experience designing, building, and operating large-scale distributed data systems.
• Deep expertise in stream processing, declarative query execution, pipeline orchestration, or data transformation at scale.
• Strong computer science fundamentals in distributed systems, algorithms, fault tolerance, and consistency models.
• Proficiency in C++ or Java with systems-level reasoning capabilities.
• Proven ability to lead cross-team technical initiatives from architecture through production at petabyte scale.
• Strong written and verbal communication skills for representing complex technical trade-offs.

Preferred Qualifications

• Experience with major analytical DBMS such as Snowflake, BigQuery, Redshift, Databricks, or Teradata.
• Hands-on background in streaming or event-driven systems like Flink, Kafka, or Spark Structured Streaming.
• Familiarity with the data engineering ecosystem including dbt, Airflow, Fivetran, Iceberg, or Delta Lake.
• Experience with CDC, change propagation, or incremental computation patterns.
• Advanced degree (MS or PhD) in Computer Science with an emphasis on databases or distributed systems.

About the Company

Snowflake is powering the era of the agentic enterprise, building the foundational cloud data platform that enables customers to move, shape, and maintain data at scale.