Role at a glance
- Salary
- $182.4K – $247K/yr
- Location
- Seattle, Washington, United States
- Work arrangement
- On-site
- Employment
- Full-time
- Experience
- 8+ years building related systems — big-data ecosystems, Apache Spark, or database internals
- Education
- BS (or higher) in Computer Science or a related technical field, or equivalent practical experience
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Role Summary
The Staff Engineer will drive the technical direction of Spark Structured Streaming across Apache Spark and the Databricks Data Intelligence Platform. The role focuses on advancing stream processing capabilities and architecture to improve latency, throughput, cost, and production operability.
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, including state management, new operators, and architectural improvements
- Build software that is high quality and easy to run in production
- Drive stream processing adoption across the Databricks product portfolio
- Guide long-term architecture and technical-debt decisions against the product roadmap
- Mentor and technically lead engineers on the team, and partner with the Engineering Manager to attract and grow talent
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
BS (or higher) in Computer Science or a related technical field, or equivalent practical experience; 8+ years building related systems in big-data ecosystems, Apache Spark, or database internals; 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.
Required
- Passion for database systems, storage systems, distributed systems, language design, or performance optimization
- Comfortable working toward a multi-year vision with incremental deliverables
Original job description
Content provided by the employer
Original job description
Content provided by the employer
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.
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.
About the company
Databricks
Large Enterprise
Databricks is a cloud-based data platform that specializes in providing solutions for data engineering, machine learning, and analytics. Founded in 2013 by the original creators of Apache Spark, the company enables organizations to unify data processing and analysis workflows, facilitating collaboration for data professionals. Databricks offers an integrated environment for data scientists, engineers, and business analysts, streamlining the process of building and deploying AI and data-driven applications. With a strong emphasis on simplifying big data management, Databricks helps businesses harness the power of their data to drive innovation and insights.
Databricks is a cloud-based data platform that specializes in providing solutions for data engineering, machine learning, and analytics. Founded in 2013 by the original creators of Apache Spark, the company enables organizations to unify data processing and analysis workflows, facilitating collaboration for data professionals. Databricks offers an integrated environment for data scientists, engineers, and business analysts, streamlining the process of building and deploying AI and data-driven applications. With a strong emphasis on simplifying big data management, Databricks helps businesses harness the power of their data to drive innovation and insights.