Senior Data Engineer

Details

NVIDIA's Digital Marketing Operations team is seeking a Senior Data Engineer to help build shared data infrastructure that powers customer engagement, campaign intelligence, and marketing analytics at scale. The 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 support audience segmentation, campaign performance measurement, privacy-compliant data activation, identity resolution, and the continued growth of NVIDIA's marketing technology ecosystem.

Responsibilities

• 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 requirements related to scale, reliability, performance, privacy compliance, security, cost, and compatibility.
• Lead complex, cross-functional initiatives across engineering, marketing, and operations stakeholders. 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 at scale.
• Build reliable, maintainable systems using 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 with system owners to establish root cause, drive resolution, and implement preventive improvements.
• Embed privacy and compliance by design across the data platform, including data governance, consent propagation, GDPR and PIPL compliance controls, data minimization, access boundaries, right-to-erasure workflows, and auditable data lineage.
• Establish robust data models, semantics, ownership boundaries, and serving interfaces across teams. Deliver trusted data assets for 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.

Requirements

• 8+ years of relevant industry experience with a Bachelor's degree or equivalent experience, and a Master's degree or equivalent in Computer Science, Engineering, or a related field.
• Sustained experience designing, implementing, and operating production data pipelines, data platforms, or distributed data systems, including end-to-end ownership of a multi-pipeline domain or 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 with cloud data platform services, including object storage, cloud data warehouses, managed transformation services, and related infrastructure.
• Experience with data lake and lakehouse architectures, including open table formats such as Apache Iceberg.
• Strong SQL and NoSQL skills and data-modeling proficiency, including query execution, incremental processing, schema evolution, consistency, analytical consumption patterns, idempotency, replay, late-arriving data, partial failure, and cross-system correctness.
• Experience building systems that move customer, behavioral, consent, campaign, or audience data across multiple platforms, with strong attention to data quality, governance, and operational reliability.
• Demonstrated ability to diagnose production failures across distributed systems by analyzing logs, metrics, traces, query plans, and profiles, followed by implementing and validating long-lasting resolutions.
• Strong architectural judgment when assessing tradeoffs among reliability, performance, cost, privacy, compatibility, and maintainability.
• Experience guiding major migrations or architectural changes across teams without interrupting production service.

Preferred Qualifications

• Experience with MarTech stacks and B2C customer data at scale, including CDP integrations, reverse ETL, identity resolution, customer 360 or profile services, audience activation pipelines, campaign metadata, tracking code management, and multi-touch attribution.
• Experience designing and operating high-throughput, fault-tolerant streaming systems at scale, including exactly-once delivery semantics, consumer lag management, schema registry patterns, and replay strategies for large data volumes.

Compensation and Benefits

• Base salary range: USD 168,000–270,250 per year, determined by location, experience, and the pay of employees in similar positions.
• Eligible for equity and benefits.
• Applications will be accepted at least until October 23, 2026.
• NVIDIA is an equal opportunity employer and is committed to fostering an inclusive work environment.