1 day ago
Base Salary
$228k - $339k/yr
Responsibilities
- Research, design, implement, and deliver logical and physical query plan optimization techniques for massively parallel data processing engines.
- Develop query planning and optimization techniques for execution engines using heterogeneous CPU- and GPU-based compute elements.
- Integrate DataPelago acceleration and plan optimization capabilities with Apache Spark, Apache Flink, and other open-source engines.
- Ensure product performance across customers’ real deployment environments and workloads.
- Establish and improve metrics for plan quality, workload performance, and reliability in customer deployments.
- Provide technical leadership through product development and post-production support while owning major components and capabilities.
- Collaborate with engineering and product management on product features, architecture, interfaces, and timelines.
- Mentor junior team members.
Requirements
- Bachelor’s degree in computer science required; a master’s degree or PhD, particularly in database systems, is preferred.
- 15+ years of experience developing query planning and query optimization techniques for enterprise data processing software platforms.
- At least 5 years of experience on parallel platforms such as Apache Spark, Presto/Trino, or Apache Flink is preferred.
- Deep knowledge of SQL semantics and expertise in SQL processing; Python processing experience is preferred.
- Strong understanding of databases, data warehouses, and query engines.
- Deep knowledge of modern query optimization from published literature and open-source software; open-source contributions or publications are preferred.
- Understanding of the architecture, deployment, and operations of data processing platforms used for data engineering, data preparation, and analytics.
- Proficiency across software development and post-production support for enterprise software or SaaS.
- Experience defining and delivering major product capabilities through technical leadership across multiple teams.
- Strong collaboration and communication skills, with the ability to adopt AI effectively.
Benefits
- Comprehensive benefits package that may include health insurance, life insurance, retirement or pension plans, paid time off, leave options, performance-based incentives, employee stock purchase plans, and restricted stock units.
- Benefits and offerings vary by country and region and are subject to local laws, regulations, and company policies.
Tech Stack
Categories
Data Engineering
About NetApp
NetApp builds data storage and data management software and hardware for enterprises, including ONTAP-powered all-flash arrays and hybrid cloud services that integrate with AWS, Azure, and Google Cloud. It sells systems and subscriptions that support backup, disaster recovery, databases, and container/Kubernetes workloads. Founded in 1992 and headquartered in San Jose, California, NetApp is a public company listed on NASDAQ.