$135K - $181K/yr
Our OSS RAPIDS Spark library is integrated with on-premise and cloud services such as AWS EMR, Databricks, Google Dataproc, Oracle Cloud Data Flow, Bytedance Volcengine, Tencent Cloud and Cloudera.
$135K - $181K/yr
Our OSS RAPIDS Spark library is integrated with on-premise and cloud services such as AWS EMR, Databricks, Google Dataproc, Oracle Cloud Data Flow, Bytedance Volcengine, Tencent Cloud and Cloudera.
$23.7K - $26.2K
0% of jobs
$26.2K - $28.7K
2% of jobs
$28.7K - $31.2K
2% of jobs
$33.6K is the 25th percentile. Wages below this are outliers.
$31.2K - $33.7K
22% of jobs
The median wage is $35.1K / yr.
$33.7K - $36.2K
43% of jobs
$36.2K - $38.7K
2% of jobs
$40.1K is the 75th percentile. Wages above this are outliers.
$38.7K - $41.3K
6% of jobs
$41.3K - $43.8K
5% of jobs
$43.8K - $46.3K
5% of jobs
$46.3K - $48.8K
4% of jobs
$48.8K - $51.3K
7% of jobs
$23.7K
$38K
$51.3K
A Databricks job is a way to run an automated workload, such as a data pipeline, machine learning model training, or ETL task, on the Databricks platform. Jobs can be scheduled, triggered manually, or run as part of a workflow. They support different task types, including notebooks, Python scripts, JARs, and SQL queries. Databricks jobs also allow for dependency management and orchestration across multiple tasks within a workflow.
To thrive in a Databricks role, you need strong programming skills in languages such as Python or Scala, a deep understanding of data engineering or data science principles, and typically a relevant degree in computer science or a related field. Experience with Apache Spark, cloud platforms like Azure or AWS, and Databricks-specific certifications are often highly valued. Exceptional problem-solving, communication, and collaboration skills help professionals excel within multidisciplinary data teams. These capabilities are crucial for successfully designing, developing, and optimizing large-scale data solutions in a fast-evolving analytics environment.
Professionals in Databricks roles typically spend their days developing and maintaining data pipelines, analyzing large datasets, and collaborating with business stakeholders to translate requirements into scalable solutions. They often use tools such as Apache Spark and cloud platforms to design and optimize workflows, while troubleshooting data quality or performance issues that arise. Regular teamwork with data engineers, analysts, and software developers is common, as is participating in sprint planning or code review sessions. Overall, the role combines hands-on technical work with ongoing collaboration to ensure data-driven insights and infrastructure reliability.
9.6
Based on 17 frontline employees who took The Breakroom Quiz
8th of 242 rated software companies
NVIDIA is seeking a Sr. Principal Systems Software Engineer for the Apache Spark Acceleration group. GPU accelerated data processing has moved from proof of concept to production deployments. Enterprises now recognize the need for accelerated computing to handle large data processing needs. Multi-node GPU deployments will reduce cloud computing costs and lower latency batch ETL workloads.
At NVIDIA, we have been invested in accelerating Apache Spark, providing an open source plugin for Apache Spark. Apache Spark is the most popular data processing engine in data centers. We strive to accelerate Spark applications on GPUs without any code changes. Our OSS RAPIDS Spark library is integrated with on-premise and cloud services such as AWS EMR, Databricks, Google Dataproc, Oracle Cloud Data Flow, Bytedance Volcengine, Tencent Cloud and Cloudera. We are passionate about working on hard problems that have an impact. You will need to have strong programming skills, a deep understanding of software development related. You will work with a team that is using open source libraries like cuDF to accelerate reading, writing and batch data operations in Spark.
What you'll be doing:
Develop Java, Scala and CUDA/C++ libraries to accelerate DataFrames and I/O operations on common file formats such as Parquet, ORC and JSON
Enable interoperability with table formats such as Apache Iceberg and Delta Lake, and metastores such as Unity Catalog
Work with open source communities to enhance libraries like NVIDIA cuDF, CCCL and UCX through technical discussion and code contributions
Collaborate with distributed systems teams to craft solutions to distributed processing problems challenges at large scale
Provide recommendations and feedback to teams regarding decisions surrounding topics such as infrastructure, continuous integration and testing strategy
Build, test and optimize CUDA/C++ libraries across different platforms
What we need to see:
BS, MS, or PhD in Computer Science, Computer Engineering, or closely related field (or equivalent experience)
15+ years of work experience in software development
Outstanding technical skills in designing and implementing high-quality distributed systems
Excellent programming skills in C++, Java, and/or Scala
Ability to work with teams across organizational boundaries and geographies
Familiarity with the open source data platform ecosystem (Apache Spark, Velox, Presto, Apache Arrow, Apache DataFusion, etc.). Meaningful contributions to the OSS community a plus.
Highly motivated with strong interpersonal skills
Database query optimization is a strong plus
You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.#deeplearning
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NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.
Computer and electronic product manufacturing
10,000+ Employees
Santa Clara, CA, US
1993
