Engineering Manager - Streaming

P-1110

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 use deep data insights to improve their business.

We are the “Spark™ Structured Streaming” team responsible for building Stream Processing capabilities into Spark™ and Databricks Intelligence Platform. Stream processing is in its infancy and we are here to build not just state of the art Stream Processing technology but best in class managed offering for customers to run their Stream Processing workloads.

We're seeking a dedicated Engineering Leader to spearhead Spark™ Structured Streaming development initiatives, encompassing both open source and Databricks-specific components. Your primary mission will be to make Spark™ Structured Streaming state of the art Stream Processing engine, by adding advanced features such as sophisticated state management, new operators and at the same time making the engine performance both from latency and throughput point of view by reimagining engine architecture.

The key responsibilities include:

• Leading a talented engineering team in Spark™ Structured Streaming team developing and promoting the engine in OSS and the Databricks Data Intelligence Platform
• Overseeing sustained recruitment of top-tier talent, and upskilling talent on the team
• Implementing robust processes to efficiently execute product vision, strategy, and roadmap in alignment with organizational goals and priorities
• Build software that is not just high quality but easy to operate.
• Make company wide impact by driving Stream Processing adoption across the Databricks product portfolio
• Manage technical debt, including long term technical architecture decisions and balance product roadmap

What we look for:

• 5+ years experience working in a related system, streaming, query processing, query optimization, including big-