出海雷达

Senior Data Engineer

开发工程限定地区(需当地身份)
公司NVIDIA
薪资$168,000 - $270,250/年
工作地点Canada, United States
地域资格限定地区(需当地身份)
时区要求日间重叠约 9 小时,基本正常作息
用工类型Full Time
发布时间今天
数据来源Himalayas
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注意地域限制:该职位明确限定在 Canada、United States 招聘。如果你是位于中国大陆的求职者,通常需要当地工作身份才能投递,或需与雇主确认是否接受独立合同(Contractor)形式合作。
关于本页中文:职位描述由本机离线模型翻译,属机器翻译,供快速判断用;正式沟通与投递请以英文原文为准。官方翻译通道恢复后会自动重译升级。

据 NVIDIA 的数字营销运营团队寻求一名高级数据工程师,帮助建立支持客户参与,竞选智能和规模化营销分析的共享数据基础设施。我们的数据平台将客户行为信号,受众定义,同意记录,竞赛元数据和激活输出转换为全球市场营销,分析,个性化,竞赛运营以及区域团队的可信,管理数据产品。这些产品使得观众分区,竞赛绩效测量,隐私合规数据激活,身份解决方案以及 NVIDIA 营销技术生态系统持续增长成为可能。我们很想让你今天申请!你将做什么:· 拥有数字营销运营中的关键数据域,包括管道,数据产品,观众服务和消费者团队。在预测规模,可靠性,性能,隐私合规,安全,成本和兼容性的需求时塑造其架构和界面。· 领导复杂的跨功能倡议。在工程,市场和运营利益相关方之间合作,将要求转化为清晰的数据架构,在关键途径中写高质量的代码,并安全地推动集成到生产中。· 构建,实施和发展批量和流媒体管道,以吸收,转化,调整并提供规模上的客户行为,观众,竞选活动,同意和激活数据。建立可靠的可维护系统,利用分布式处理框架,工作流配套工具,云数据仓库,对象存储以及公 pub/sub 消息平台。· 构造和开发共享数据质量框架和工程标准,提高管道可靠性,一致性和效率。· 在团队中领导生产事件调查在管道,分布式处理,存储和云服务上。协调系统所有者建立根源,推动解决方案和实施预防性改进。· 将隐私与合规性嵌入数据平台的设计中。实现并执行数据治理,同意传播,GDPR 和 PIPL 合规控制,数据最小化,访问界限,权删除工作流程以及可审核的数据谱系作为一流工程要求,而不是后期思考。·建立强大的数据模型,语义学,拥有权界限和跨团队服务接口。

查看英文原文

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 at scale. Our 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. We would love for you to apply today!
What You'll Be Doing:

  • 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 at scale. Build 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.

What We Need To See:

  • 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 with cloud data platform services, including object storage, cloud data warehouses, managed transformation services, and related infrastructure. Demonstrated ability to architect and operate large-scale data workflows in a cloud environment.
  • Experience with data lake and lakehouse architectures, including open table formats such as Apache Iceberg. Ability to design, manage, and optimize large-scale data storage for reliable analytical consumption.
  • Strong SQL and NoSQL skills and data-modeling proficiency, including practical depth in 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 skill in diagnosing 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 in assessing tradeoffs among reliability, performance, cost, privacy, compatibility, and maintainability. Experience guiding major migrations or architectural changes across teams without interrupting production service.

Ways To Stand Out From The Crowd:

  • 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.

NVIDIA is widely considered to be one of the technology world’s most desirable employers! We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you!
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 168,000 USD - 270,250 USD.You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until October 23, 2026.This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.Originally posted on Himalayas

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