Position Details
About this role
This role involves developing and managing high-throughput data pipelines and data lakehouse infrastructure to support NVIDIA's AI and research teams, ensuring scalable and reliable data operations.
Key Responsibilities
- Build scalable data pipelines
- Architect Data Lakehouse
- Implement automation and data governance
- Collaborate with engineering teams
- Optimize data schemas and performance
Technical Overview
The technical environment includes Python, Java, Spark, Kafka, Kubernetes, and modern data lakehouse formats like Iceberg, Delta Lake, and Hudi, focusing on scalable data architecture and governance.
Ideal Candidate
The ideal candidate is a senior data engineer with at least 8 years of experience in building scalable data pipelines and managing data lakehouse architectures, proficient in Python, Java, Spark, and Kafka, with strong leadership and problem-solving skills.
Must-Have Skills
Nice-to-Have Skills
Tools & Platforms
Required Skills
Hard Skills
Soft Skills
Industry & Role
Keywords for Your Resume
Deal Breakers
Less than 8 years of experience in Data Engineering, Lack of experience with Kafka or Spark, No familiarity with Data Lakehouse architectures, Inability to work with Kubernetes or distributed systems
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