Senior Data Engineer

NVIDIA's Digital Marketing Operations team is seeking a Senior Data Engineer to help build the shared data infrastructure that powers customer engagement, campaign intelligence, and marketing analytics  data platform transforms customer behavioral signals, audience definitions, consent records, campaign metadata, and activation outputs into trusted, governed data products for marketing, analytics, personalization, campaign operations, and regional teams worldwide. These products enable audience segmentation, campaign performance measurement, privacy-compliant data activation, identity resolution, and the continued growth of NVIDIA's marketing technology ecosystem.

Own a key data domain within Digital Marketing Operations, spanning pipelines, data products, audience services, and consumer teams. Shape its architecture and interfaces while anticipating needs related to scale, reliability, performance, privacy compliance, security, cost, and compatibility. Lead complex, cross-functional initiatives. Collaborate across engineering, marketing, and operations stakeholders to translate requirements into clear data architectures, write high-quality code in the critical path, and drive integrations safely into production.

Architect, implement, and evolve batch and streaming pipelines that ingest, transform, reconcile, and serve customer behavioral, audience, campaign, consent, and activation data ld reliable, maintainable systems leveraging distributed processing frameworks, workflow orchestration tools, cloud data warehouses, object storage, and pub/sub messaging platforms. Build and evolve shared data quality frameworks and engineering standards that improve pipeline reliability, consistency, and efficiency across teams.

Lead production incident investigations across pipelines, distributed processing, storage, and cloud services. Coordinate across system owners to establish root cause, drive resolution, and implement preventive improvements. Embed privacy and compliance by design across the data platform. Implement and enforce data governance, consent propagation, GDPR and PIPL compliance controls, data minimization, access boundaries, right-to-erasure workflows, and auditable data lineage as first-class engineering requirements, not afterthoughts.

Establish robust data models, semantics, ownership boundaries, and serving interfaces across teams. Deliver trusted data assets that make customer and campaign data widely accessible to marketing consumers without sacrificing accuracy, privacy, or maintainability. Provide technical leadership through architecture and data model reviews, hands-on mentorship of junior engineers, and evidence-based resolution of difficult tradeoffs. Raise engineering quality across teams through reusable patterns, clear decisions, and sustained follow-through.

8+ years of relevant industry experience with a Bachelor's or equivalent experience, and a Master's degree or equivalent in Computer Science, Engineering, or a related field. A sustained record of designing, implementing, and operating production data pipelines, data platforms, or distributed data systems. This includes end-to-end technical ownership of a multi-pipeline domain or a complex cross-team data engineering initiative. Proficiency in Python and one or more modern programming languages such as Java or Golang, with strong SQL fundamentals and the ability to write clean, testable, production-quality code.

Deep hands-on experience with distributed data processing frameworks such as Apache Spark, and cloud-managed ETL services. Experience building and operating production pipelines with workflow orchestration tools such as Airflow or equivalent. Strong experience…