RDQ326R93
Databricks is radically simplifying the entire data lifecycle, from ingestion to generative AI and everything in-between. We’re doing it cross-cloud with a unified platform, serving over 10k customers, processing exabytes of data/day on 15+ million VMs, and growing exponentially.
The Lakeflow team is looking for recent PhD graduates. Lakeflow team includes products like Apache Spark™ Structured Streaming, Delta Live Tables (DLT), and Materialized Views. Apache Spark™ Structured Streaming is one the world’s most popular streaming engines. DLT makes it easy to build and manage reliable batch and streaming data pipelines that deliver high-quality data on the Databricks Lakehouse Platform. DLT helps data engineering teams simplify ETL (extract-transform-load) development and management with declarative pipeline development, automatic data testing, and deep visibility for monitoring and recovery. DLT optimizes pipeline execution by logical optimization through query transformations, and physical optimization such as instance type selection and vertical/horizontal autoscaling.
Moreover, as part of DLT, we have a new catalyst optimization layer, Eenzyme, designed specifically to speed up the ETL process and make declarative ETL computation possible by incrementally computing and materializing the intermediate results. Enzyme can create and keep up-to-date a materialization of the results of a given query stored in a Delta table. Enzyme does this by using a cost model to choose between a variety of techniques that borrow from traditional literature on the maintenance of materialized views, delta-to-delta streaming, and manual ETL patterns commonly used by our customers.
As a part of the LakeflowDLT team, there are opportunities to design and implement in many areas that leapfrog existing systems:
- Query compilation and optimization
- Distributed query execution and scheduling
- Vectorized engine execution
- Resource Management
- Transaction coordination
- Efficient storage structures (encoding, indexes)
- Automatic physical data optimization
What We Look For:
- PhD in databases or systems
- Knowledge of database systems, storage systems, distributed systems, and performance optimization
- Motivated by delivering customer value and influence
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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 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.
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, please visit https://www.mybenefitsnow.com/databricks.
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.
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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.
Top Skills
What We Do
As the leader in Unified Data Analytics, Databricks helps organizations make all their data ready for analytics, empower data science and data-driven decisions across the organization, and rapidly adopt machine learning to outpace the competition. By providing data teams with the ability to process massive amounts of data in the Cloud and power AI with that data, Databricks helps organizations innovate faster and tackle challenges like treating chronic disease through faster drug discovery, improving energy efficiency, and protecting financial markets.
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