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. About Dynamic Tables Dynamic Tables (DTs) are Snowflake's declarative streaming transformation primitive. Customers define a SQL query and a freshness target; Snowflake handles the rest: orchestrating refreshes, maintaining snapshot consistency across a DAG of dependencies, and automatically incrementalizing the computation so that cost scales with what changed. Dynamic Tables is one of the fastest growing products at Snowflake and is a core part of Snowflake’s Data Engineering strategy. The Dynamic Tables performance team is responsible for making incremental refresh fast, predictable, and cost-efficient across increasingly complex query shapes. As a Staff Engineer on this team, you will own the technical direction for critical performance initiatives and be a force multiplier for the engineers around you. What You'll Do Lead the design and implementation of performance improvements to the incremental view maintenance engine, including multi-join incrementalization, novel incrementalization semantics, incremental window functions, and stacked operations. Help define the roadmap for the incremental view maintenance engine, identifying key performance, scalability, and correctness milestones, prioritizing high-impact enhancements, and aligning technical investments with prod
Role overview
Job description
At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can turn deep data insights into better business outcomes. We are the Spark Structured Streaming team, responsible for building stream processing into Apache Spark and the Databricks Data Intelligence Platform. Stream processing is still in its early days, and we're here to build not only state-of-the-art streaming technology but also a best-in-class managed offering for customers to run their streaming workloads. The role We're seeking an experienced Staff Engineer to drive the technical direction of Spark Structured Streaming, spanning both open source and Databricks-specifi
…What they are looking for
Skills & requirements
Qualification
government license for such positions, and Employer may decline to proceed with an applicant on this basis alone
Department · Engineering - Pipeline
Hiring company
Databricks
Databricks offers a unified platform for data, analytics and AI. Build better AI with a data-centric approach. Simplify ETL, data warehousing, governance and AI on the Data + AI Platform.
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