Role at a glance
- Salary
- $166K – $225K/yr
- Location
- Mountain View, California, United States San Francisco, California, United States
- Work arrangement
- On-site
- Employment
- Full-time
- Experience
- 5+ years of experience working in a related system (preferred)
- Education
- Optional: PhD in databases or distributed systems
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Role Summary
This role contributes to Databricks’ next-generation query engine and structured storage system for the Lakehouse platform. The work focuses on improving relational query performance while supporting workloads ranging from ETL to data science.
What You'll Do
- Design and implement query compilation and optimization systems
- Develop distributed query execution and scheduling
- Build vectorized execution engines
- Work on data security, resource management, and transaction coordination
- Develop efficient storage structures including encodings and indexes
- Implement automatic physical data optimization
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
Passion for database systems, storage systems, distributed systems, language design, or performance optimization; experience working towards a multi-year vision with incremental deliverables; motivated by delivering customer value and impact.
Preferred
- 5+ years of experience working in a related system
- PhD in databases or distributed systems
Original job description
Content provided by the employer
Original job description
Content provided by the employer
Our mission at Databricks is to radically simplify the whole data lifecycle from ingestion to ETL, BI, and all the way up to ML/AI with a unified platform. To achieve this goal, we believe the data warehouse architecture as we know it today will be replaced by a new architectural pattern, Lakehouse (CIDR 2021 paper), open platforms that unify data warehousing and advanced analytics. The new architecture will help address several major challenges, including data staleness, reliability, total cost of ownership, data lock-in, and limited use-case support.
A critical part of realizing this vision is the next generation (decoupled) query engine and structured storage system that can outperform specialized data warehouses in relational query performance, yet retain the expressiveness and of general purpose systems such as Apache Spark™ to support diverse workloads ranging from ETL to data science.
As part of this team, you will be working in one or more of the following areas to design and implement these next gen systems that leapfrog state-of-the-art:
- Query compilation and optimization
- Distributed query execution and scheduling
- Vectorized execution engine
- Data security
- Resource management
- Transaction coordination
- Efficient storage structures (encodings, indexes)
- Automatic physical data optimization
What we look for:
- A passion for database systems, storage systems, distributed systems, language design, or performance optimization
- Experience working towards a multi-year vision with incremental deliverables
- Motivated by delivering customer value and impact
- 5+ years of experience working in a related system (preferred)
- Optional: PhD in databases or distributed systems
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.