Staff Software Engineer - Streaming

Databricks is the Data and AI company, building the world's best data and AI infrastructure platform. More than 20,000 organizations rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics, and agents.

We are the Spark Structured Streaming team, responsible for building stream processing into Apache Spark and the Databricks Data Intelligence Platform. We're seeking an experienced Staff Engineer to drive the technical direction of Spark Structured Streaming, spanning both open source and Databricks-specific components.

• Set and drive the technical vision for Spark Structured Streaming across OSS and the Databricks Data Intelligence Platform
• Design and build core engine capabilities — state management, new operators, and architectural improvements to latency and throughput
• Raise the bar for engineering quality and operability
• Make company-wide impact by driving stream processing adoption
• Guide long-term architecture and technical-debt decisions
• Mentor and technically lead engineers, and partner with the Engineering Manager to attract and grow top-tier talent

• BS (or higher) in Computer Science or a related technical field, or equivalent practical experience
• 8+ years building related systems — big-data ecosystems, Apache Spark, or database internals
• A passion for database systems, storage systems, distributed systems, language design, or performance optimization
• Comfortable working toward a multi-year vision with incremental deliverables
• A track record of delivering features while maintaining a high bar for operational excellence
• Comfortable working cross-functionally with product management and directly with customers

Local Pay Range: $182,400—$247,000 USD. The total compensation package may also include eligibility for annual performance bonus, equity, and benefits.

Equity and annual performance bonus are mentioned. For specific benefits details, refer to the company's regional benefits page.

Apply via the provided link.