NVIDIA is looking for a Data Analysis Technical lead to join Networking Clusters Solutions group. In this role, you will be responsible to define advance data analysis architecture scheme for our clusters’ performance analysis, cluster management and monitoring solutions. You will dive into emerging technologies, define and prove concepts, and identify or create the necessary frameworks. Your responsibilities will include defining and implementing large-scale telemetry pipelines, ensuring data integrity, and designing simulation solutions and other innovative technologies. You will also design and optimize data architecture to support robust and scalable systems. Networking Cluster Solutions (NCS) group is responsible to build the biggest AI clusters in NVIDIA Israel to qualify and optimize NVIDIA Networking solutions at scale.
What You'll Be Doing:
Define and implement the group’s data analytics technical roadmap, ensuring alignment with teams inside and outside the group
Oversee the quality, performance, and maintainability of the data analytics codebase and delivered solutions
Drive best practices in software engineering, data modelling, data quality, code quality, security, observability, and operational excellence
Build high-performance ETL pipelines with advanced data integrity control of NCS group
Define and build NCS group different ETL pipelines and reports for HPC & AI clusters’ performance, telemetry and E2E tests coverage
What We Need To See:
BSc. or MSc. in Computer Engineering or Computer Science
10+ years of experience in development
Experience with modern analytic tools and platforms such as Spark, Data Bricks, etc.
Perfect understanding of telemetry solutions at scale and automation technologies, along with modern application platforms and paradigms
Advanced coding skills agnostic to development languages and tools, from ETL pipelines to standalone solutions
Ways To Stand Out From The Crowd:
Familiarity with cloud-native development and deployment methodologies
Experience with public cloud solutions (AWS, GCP, Azure)
Background in data center design and technologies
Experience with large-scale data processing systems
Existing contributions to open-source communities
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