Distinguished Engineer, Apache Spark

Nvidia•Santa Clara, CA

50d

About The Position

NVIDIA is seeking a Distinguished Engineer for the Apache Spark Acceleration group. Over the past five years GPU accelerated data processing has moved from proof of concept to production deployments. Many enterprises are now recognizing the needs of accelerated computing for large scale data processing. Multi-node GPU deployments will reduce cloud computing costs and lower latency of large scale data processing. 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. You will serve as a hands-on architect of Nvidia Spark Acceleration Group. You will work with a team of distributed system engineers including PMC and Committers of Apache Spark, Apache Hadoop, Apache Hive, and Apache Arrow. You will engage in open source projects such as Apache Spark, RAPIDS, Apache Iceberg, Delta Lake, UCX and more.

Requirements

BS, MS, or PhD in Computer Science, Computer Engineering, or closely related field (or equivalent experience)
17+ years of work or research experience in software development
Prior experience in delivering complex software projects as a lead architect
Outstanding technical skills in designing and implementing high-quality distributed systems
Excellent programming skills in C++, Java, and/or Scala
Highly motivated with strong interpersonal skills and communication skills
5+ years working experience with key open source big-data projects as a contributor or committer to Apache Spark, Apache Hadoop, Apache Flink, Apache Kafka, Apache Hive, Apache Arrow, Delta Lake
Excellent knowledge about distributed system schedulers: Kubernetes, Hadoop YARN, Apache Spark
Able to delve into a new area and quickly come up to speed
Able to work with teams across boundaries and geographies

Nice To Haves

Working experience in designing and developing columnar query engines would be a huge plus
Committership at major open source projects (such as Apache Spark, Apache Hadoop, Apache Flink) is a big plus
Working experience with acceleration libraries (CUDA, RAPIDS, UCX) is helpful

Responsibilities

Lead the architecture, design and implementation of accelerated Apache Spark and related big-data frameworks
Engage open source communities (including Apache Spark, RAPIDS, Apache Iceberg, Delta Lake and UCX) for technical discussion and contribution, and engage new communities where we may not have a strong presence yet
Work with NVIDIA partners to deploy GPU enabled data analytics solutions in public cloud or on-premises clusters
Present technical solutions at industry conferences and meetups
Collaborate with distributed systems teams to define 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
Build automation and tools that will increase the productivity of teams developing distributed systems
Mentor members of the engineering team