✦ Luna Orbit — Data & Analytics

Senior System Software Engineer - Data Engineering

at Nvidia

📍 2 Locations Unknown Posted March 13, 2026
Type Full-Time
Experience senior
Exp. Years 8+ years
Education BS or MS in Computer Science, Electrical Engineering, or related field
Category Data & Analytics

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.

  • Build scalable data pipelines
  • Architect Data Lakehouse
  • Implement automation and data governance
  • Collaborate with engineering teams
  • Optimize data schemas and performance

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.

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.

PythonJavaSparkKafkaKubernetesData Lakehouse
FlinkApache IcebergDelta LakeHudiData governance
KubernetesApache IcebergDelta LakeHudiKafkaSparkFlink
PythonJavaSparkKafkaKubernetesData LakehouseApache IcebergDelta LakeHudiStreaming architectureData pipelinesData governanceSchema design
PythonJavaSparkFlinkKubernetesData LakehouseApache IcebergDelta LakeHudiKafkaStreaming architectureData pipelinesData governanceSchema design
CollaborationProblem-solvingAutonomyLeadershipCommunication
Industry Technology / AI & Machine Learning
Job Function Developing and maintaining scalable data infrastructure for NVIDIA's AI and research data needs
Senior System Software EngineerData EngineeringData LakehouseApache IcebergDelta LakeHudiKafkaSparkFlinkKubernetesStreaming architectureData pipelinesData governanceSchema designPythonJava

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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