Experience: 5+ years
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.
Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location.
Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here .
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This posting was published by Databricks on their own careers system and is shown here with a direct link to apply there. Employers: for corrections or removal, contact jobs@veritahire.com.