Databricks
Staff Software Engineer - Distributed Data Systems
Databricks, Mountain View, California, us, 94039
Staff Software Engineer - Distributed Data Systems
P-186
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At Databricks, we are obsessed with enabling data teams to solve the world’s toughest problems, from security threat detection to cancer drug development. We do this by building and running the world’s best data and AI infrastructure platform, so our customers can focus on the high‑value challenges that are central to their own missions.
Founded in 2013 by the original creators of Apache Spark™, Databricks has grown from a tiny corner office in Berkeley, California to a global organization with over 1,000 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission‑critical workloads, making us one of the fastest growing SaaS companies in the world.
Our engineering teams build highly technical products that fulfill real, important needs in the world. We constantly push the boundaries of data and AI technology, while simultaneously operating with the resilience, security and scale that is critical to making customers successful on our platform.
We develop and operate one of the largest‑scale software platforms. The fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day. At our scale, we regularly observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above.
Modern data analysis employs sophisticated methods such as machine learning that go well beyond the roll‑up and drill‑down capabilities of traditional SQL query engines. As a software engineer on the Runtime team at Databricks, you will be building the next‑generation distributed data storage and processing systems that can outperform specialized SQL query engines in relational query performance, yet provide the expressiveness and programming abstractions to support diverse workloads ranging from ETL to data science.
Example Projects
Apache Spark™ : Develop the de‑facto open‑source standard framework for big data.
Data Plane Storage : Deliver reliable and high‑performance services and client libraries for storing and accessing massive amounts of data on cloud storage backends, e.g., AWS S3, Azure Blob Store.
Delta Lake : A storage management system that combines the scale and cost‑efficiency of data lakes, the performance and reliability of a data warehouse, and the low latency of streaming. Its higher‑level abstractions and guarantees, including ACID transactions and time travel, drastically simplify the complexity of real‑world data engineering architecture.
Delta Pipelines : Simplify the management of data engineering pipelines, enabling orchestration and operation of thousands of pipelines with higher‑level abstractions for expressing pipelines.
Performance Engineering : Build the next‑generation query optimizer and execution engine that is fast, tuning‑free, scalable, and robust.
What We Look For
BS in Computer Science, related technical field or equivalent practical experience.
Optional: MS or PhD in databases, distributed systems.
Comfortable working towards a multi‑year vision with incremental deliverables.
Driven by delivering customer value and impact.
8+ years of production‑level experience in either Java, Scala or C++.
Strong foundation in algorithms and data structures and their real‑world use cases.
Experience with distributed systems, databases, and big data systems (Apache Spark™, Hadoop).
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: $192,000—$260,000 USD
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.
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.
Referrals increase your chances of interviewing at Databricks by 2x
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At Databricks, we are obsessed with enabling data teams to solve the world’s toughest problems, from security threat detection to cancer drug development. We do this by building and running the world’s best data and AI infrastructure platform, so our customers can focus on the high‑value challenges that are central to their own missions.
Founded in 2013 by the original creators of Apache Spark™, Databricks has grown from a tiny corner office in Berkeley, California to a global organization with over 1,000 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission‑critical workloads, making us one of the fastest growing SaaS companies in the world.
Our engineering teams build highly technical products that fulfill real, important needs in the world. We constantly push the boundaries of data and AI technology, while simultaneously operating with the resilience, security and scale that is critical to making customers successful on our platform.
We develop and operate one of the largest‑scale software platforms. The fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day. At our scale, we regularly observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above.
Modern data analysis employs sophisticated methods such as machine learning that go well beyond the roll‑up and drill‑down capabilities of traditional SQL query engines. As a software engineer on the Runtime team at Databricks, you will be building the next‑generation distributed data storage and processing systems that can outperform specialized SQL query engines in relational query performance, yet provide the expressiveness and programming abstractions to support diverse workloads ranging from ETL to data science.
Example Projects
Apache Spark™ : Develop the de‑facto open‑source standard framework for big data.
Data Plane Storage : Deliver reliable and high‑performance services and client libraries for storing and accessing massive amounts of data on cloud storage backends, e.g., AWS S3, Azure Blob Store.
Delta Lake : A storage management system that combines the scale and cost‑efficiency of data lakes, the performance and reliability of a data warehouse, and the low latency of streaming. Its higher‑level abstractions and guarantees, including ACID transactions and time travel, drastically simplify the complexity of real‑world data engineering architecture.
Delta Pipelines : Simplify the management of data engineering pipelines, enabling orchestration and operation of thousands of pipelines with higher‑level abstractions for expressing pipelines.
Performance Engineering : Build the next‑generation query optimizer and execution engine that is fast, tuning‑free, scalable, and robust.
What We Look For
BS in Computer Science, related technical field or equivalent practical experience.
Optional: MS or PhD in databases, distributed systems.
Comfortable working towards a multi‑year vision with incremental deliverables.
Driven by delivering customer value and impact.
8+ years of production‑level experience in either Java, Scala or C++.
Strong foundation in algorithms and data structures and their real‑world use cases.
Experience with distributed systems, databases, and big data systems (Apache Spark™, Hadoop).
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: $192,000—$260,000 USD
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.
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.
Referrals increase your chances of interviewing at Databricks by 2x
#J-18808-Ljbffr