Senior Data Engineer leading the design and implementation of data pipelines for NVIDIA’s analytics and monitoring systems. Collaborating across teams to enhance data ingestion and analysis capabilities.
Responsibilities
Act as the technical owner and primary point of contact for ML/AI data pipelines, large‑scale data ingestion, and enterprise data warehousing
Lead the design and onboarding of new, high‑volume data sources to continuously expand and mature the centralized Data Lake
Partner with multiple NVIDIA product and infrastructure teams to translate complex business and technical requirements into scalable data solutions
Work closely with system architects, platform engineers, and data scientists to co‑design end‑to‑end analytics and ML‑ready architectures
Design, build, and optimize high‑performance ETL pipelines with strong guarantees around data integrity, reliability, and observability
Contribute to and influence the architecture of next‑generation monitoring, telemetry, and analytics platforms for hyperscale Data Centers
Provide technical leadership and mentorship, guiding teams toward best practices in data engineering and data‑driven decision‑making
Requirements
BSc. or MSc. in Computer Science, Computer Engineering, or a related field
5+ years of hands‑on experience in Data Engineering, large‑scale telemetry systems, and big‑data platforms
Deep understanding of telemetry architectures, automation technologies, and modern application platforms and paradigms
Strong familiarity with networking fundamentals; experience in data‑center environments is a strong advantage
Proven experience with modern analytics and big‑data platforms such as Spark, Databricks, and similar ecosystems
Solid understanding of different telemetry pipeline models and trade‑offs (streaming vs. batch, push vs. pull, real‑time vs. near‑real‑time)
Advanced programming skills and a track record of building production‑grade data pipelines, tooling, and proof‑of‑concepts
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