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-data ecosystem, Apache Spark™ or database internal
• A passion for database systems, storage systems, distributed systems, language design, or performance optimization
• Can ensure the team builds high quality and reliable infrastructure services. Experience being responsible for testing, quality, and SLAs of a product. Previous experience building and leading teams in a complex technical domain, such as on distributed data systems or database internals
• Ability to attract, hire, and coach engineers who meet the Databricks hiring standards. Can up level existing team via hiring top-notch senior talent, growing leaders and helping struggling members. Can gain trust of the team and guide their careers. Experience managing distributed teams preferred
• Comfortable working cross functionally with product management and directly with customers; ability to deeply understand product and customer personas

Pay Range Transparency

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.

Local Pay Range

$181,000—$253,750 USD

Compliance

If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.