3 months ago
Base Salary
$264k - $380k/yr
Responsibilities
- Define and drive the technical direction for Snowflake’s core data engineering and streaming transformation primitives.
- Lead multi-quarter investments in performance, scalability, correctness, and reliability with measurable outcomes.
- Partner with product, research, and engineering teams to co-design composable data engineering primitives.
- Run architectural reviews, establish design-document standards, and help engineers grow through feedback and sponsorship.
- Work with customers and field teams to understand usage patterns and prioritize engineering investments.
- Contribute to Snowflake’s technical reputation through internal influence, external talks, or research publications.
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 fundamentals in distributed systems, algorithms, fault tolerance, and consistency models.
- Proficiency in C++ or Java and comfort reasoning about latency, throughput, and resource efficiency at cloud scale.
- Experience leading cross-team technical initiatives from architecture through production at petabyte scale across thousands of concurrent workloads.
- Strong written and verbal communication skills for explaining technical trade-offs to engineering, product, and leadership audiences.
- Experience with a major analytical DBMS such as Snowflake, BigQuery, Redshift, Databricks, or Teradata is preferred.
- Hands-on experience with streaming or event-driven systems such as Flink, Kafka, or Spark Structured Streaming is preferred.
- Familiarity with dbt, Airflow, Fivetran, Iceberg, or Delta Lake is preferred.
- Experience with CDC, change propagation, or incremental computation patterns is preferred.
- An advanced degree in computer science emphasizing databases or distributed systems is preferred.
Tech Stack
Amazon RedshiftApache AirflowApache FlinkApache KafkaApache SparkC++DatabricksdbtGoogle BigQueryJavaSnowflake
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.