Distributed Data Systems - Staff Software Engineer at DataBricks
San Francisco, CA
About the Job
P-186At 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 1000 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.Below are some 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 humongous amount 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: It's difficult to manage even a single data engineering pipeline
The goal of the Delta Pipelines project is to make it simple and possible to orchestrate and operate tens of thousands of data pipelines
It provides a higher level abstraction for expressing data pipelines and enables customers to deploy, test & upgrade pipelines and eliminate operational burdens for managing and building high quality data pipelines.Performance Engineering: Build the next generation query optimizer and execution engine that's 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 (Spark, Hadoop).BenefitsComprehensive health coverage including medical, dental, and vision401(k) PlanEquity awardsFlexible time offPaid parental leaveFamily PlanningGym reimbursementAnnual personal development fundWork headphones reimbursementEmployee Assistance Program (EAP)Business travel accident insuranceAbout DatabricksDatabricks is the data and AI company
More than 5,000 organizations worldwide — including Comcast, Condé Nast, H&M, and over 40% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify their data, analytics and AI
Databricks is headquartered in San Francisco, with offices around the globe
Founded by the original creators of Apache Spark, Delta Lake and MLflow, Databricks is on a mission to help data teams solve the world's toughest problems
To learn more, follow Databricks on Twitter, LinkedIn and Facebook.Our Commitment to Diversity and InclusionAt 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.Pay Range TransparencyDatabricks is committed to fair and equitable compensation practices
The pay range(s) for this role is listed below and represents base 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 utilizes 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 USDAbout DatabricksDatabricks 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.Our Commitment to Diversity and InclusionAt 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.ComplianceIf 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.
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 1000 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.Below are some 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 humongous amount 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: It's difficult to manage even a single data engineering pipeline
The goal of the Delta Pipelines project is to make it simple and possible to orchestrate and operate tens of thousands of data pipelines
It provides a higher level abstraction for expressing data pipelines and enables customers to deploy, test & upgrade pipelines and eliminate operational burdens for managing and building high quality data pipelines.Performance Engineering: Build the next generation query optimizer and execution engine that's 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 (Spark, Hadoop).BenefitsComprehensive health coverage including medical, dental, and vision401(k) PlanEquity awardsFlexible time offPaid parental leaveFamily PlanningGym reimbursementAnnual personal development fundWork headphones reimbursementEmployee Assistance Program (EAP)Business travel accident insuranceAbout DatabricksDatabricks is the data and AI company
More than 5,000 organizations worldwide — including Comcast, Condé Nast, H&M, and over 40% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify their data, analytics and AI
Databricks is headquartered in San Francisco, with offices around the globe
Founded by the original creators of Apache Spark, Delta Lake and MLflow, Databricks is on a mission to help data teams solve the world's toughest problems
To learn more, follow Databricks on Twitter, LinkedIn and Facebook.Our Commitment to Diversity and InclusionAt 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.Pay Range TransparencyDatabricks is committed to fair and equitable compensation practices
The pay range(s) for this role is listed below and represents base 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 utilizes 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 USDAbout DatabricksDatabricks 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.Our Commitment to Diversity and InclusionAt 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.ComplianceIf 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.
