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-specific components. Your mission is to make Spark Structured Streaming the state-of-the-art stream processing engine — adding advanced capabilities such as sophisticated state management and new operators, while re-imagining the engine's architecture to drive improvements for latency, throughput, and cost. What you'll do: 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, building software that is not just high quality but easy to run in production Make company-wide impact by driving stream processing adoption across the Databricks product portfolio Guide long-term architecture and technical-debt decisions, balancing them against the product roadmap Mentor and technically lead engineers on the team, and partner with the Engineering Manager to attract and grow top-tier talent What we look for: 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 and engineering quality Comfortable working cross-functionally with product management and directly with customers, with the ability to deeply understand the 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 $182,400 — $247,000 USD About Databricks Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn , X , YouTube , and Instagram . Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here . Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. 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.

Requirements

Must-haves

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, building software that is not just high quality but easy to run in production
Make company-wide impact by driving stream processing adoption across the Databricks product portfolio
Guide long-term architecture and technical-debt decisions, balancing them against the product roadmap
Mentor and technically lead engineers on the team, 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 and engineering quality
Comfortable working cross-functionally with product management and directly with customers, with the ability to deeply understand the product and customer personas
Our Commitment to Diversity and Inclusion

Nice-to-haves

None flagged.

Application prep

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Keywords to mirror

Platform: greenhouse
Effort: quick

Benefits

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Vision