出海雷达

Analytics Engineer 5 - Ads Identity & Signals

开发工程限定地区(需当地身份)
公司Netflix
薪资$330,000 - $566,000/年
工作地点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 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。

在 Netflix,我们的使命是要娱乐世界。我们一起写下一个集 - 推进故事讲述的界限,全球热爱和让难以想象的事情成为现实。我们是一个梦幻团队,沉迷于发现创造力,直觉和尖端技术融合时会发生什么不舒服的兴奋。来做下一步的一部分。在2022年,我们推出了一个新的低价广告支持层次,我们正在建立内部的,世界级的广告科技生态系统,为我们的成员提供更多选择并为广告商提供高等级,比线性电视更好的体验。我们正在寻找这个新业务领域的创始人。身份和信号团队构建了 Netflix 广告业务的身份基础。这些图形和匹配系统使我们能够识别同一个人或家庭在信号,设备和合作伙伴数据来源中,并确定我们可以负责任地使用哪些信号来目标测量和报告。我们构建和维护身份图表,运行和评估实体匹配和分辨率管道,以及与身份提供商管理关系,以便广告商和内部团队都能信任每个运动下的信号。这是一个小,高杆性的团队的基本作用。你将构建分析和数据基础设施,为身份匹配和图形建设提供动力。设计表格,管道和指标使团队及其利益相关者能够了解时间的匹配质量,覆盖率和漂移。你将从端到端工作:从原始信号摄入,通过匹配逻辑和图形构造,到让身份健康可见和可操作的仪表板和数据产品。在该角色中,你将 · 设计,建造和维护支持身份图形构建,实体匹配以及识别分辨方案在一方和第三方信号中。·与数据工程和软件工程合作,以生产匹配逻辑,确保管道可扩展,测试并监控数据质量和漂移。·建立衡量度表,仪表板和分析,以定量匹配率,匹配质量,覆盖范围和图形稳定性,并在它们影响下游活动之前对表面异常进行量化。·密切地与数据科学合作评估和改进匹配算法,提供清洁的,文档好的数据和功能,用于测试和转换所需的信息。

查看英文原文

At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what’s next.
In 2022 we launched a new lower-priced, ad-supported tier, and we are building an in-house, world-class ad-tech ecosystem to give our members more choice and to offer advertisers a premium, better-than-linear-TV experience. We are looking for the founding members of this new business area for Netflix.

The Identity & Signals team builds the identity foundation of the Netflix ads business — the graph and matching systems that let us recognize the same person or household across signals, devices, and partner data sources, and that determine which signals we can responsibly and accurately use for targeting, measurement, and reporting. We build and maintain the identity graph, run and evaluate entity-matching and resolution pipelines, and manage relationships with identity providers so that advertisers and internal teams can trust the signals underneath every campaign.

This is a foundational role on a small, high-leverage team. You will build the analytics and data infrastructure that powers identity matching and graph construction — designing the tables, pipelines, and metrics that let the team and its stakeholders understand match quality, coverage, and drift over time. You'll work end-to-end: from raw signal ingestion, through matching logic and graph construction, to the dashboards and data products that make identity health visible and actionable across the company.

In This Role, You Will

  • Design, build, and maintain the data models and pipelines that support identity graph construction, entity matching, and identity resolution across first-party and third-party signals.
  • Partner with data engineering and software engineering to productionize matching logic, ensuring pipelines are scalable, well-tested, and monitored for data quality and drift.
  • Build metrics, dashboards, and analytics that quantify match rate, match quality, coverage, and graph stability, and that surface anomalies before they affect downstream campaigns.
  • Work closely with data science to evaluate and improve matching algorithms, providing the clean, well-documented data and features needed to test and iterate on models.
  • Manage and evaluate the analytics relationship with external identity providers (e.g., Experian, TransUnion, LiveRamp), including onboarding new sources, validating match performance, and monitoring ongoing data quality.
  • Translate identity graph and matching concepts — nodes, edges, match confidence, deterministic vs. probabilistic matching — into clear, actionable insights for product, sales, and other non-technical stakeholders.
  • Collaborate with product and cross-functional partners to define identity requirements, evaluate trade-offs (accuracy vs. coverage vs. privacy), and prioritize roadmap work.
  • Communicate technical decisions, trade-offs, and results clearly to both technical and non-technical audiences at all levels of the company.

We Are Looking For

  • 5+ years of experience as an analytics engineer, data engineer, or similar role working with large-scale data.
  • Experience working with graph data structures and graph-based data models (e.g., property graphs, graph databases, or graph analytics on top of relational/columnar stores).
  • Familiarity with entity matching / identity resolution concepts — deterministic and probabilistic matching, fuzzy matching, blocking/candidate generation, and match quality evaluation.
  • Knowledge of, or direct experience working with, identity providers such as Experian, TransUnion, LiveRamp, or similar data/identity partners.
  • Strong SQL and Python skills, with experience building and maintaining production data pipelines.
  • Experience designing data models, metrics, and dashboards that make complex technical systems understandable to non-technical stakeholders.
  • Demonstrated ability to collaborate closely across data engineering, software engineering, data science, and product teams.
  • Ability to work independently, drive your own projects, and make compelling cases for prioritization.
  • Embodies the Netflix values while bringing a new perspective to continue improving our culture.

Nice To Have

  • Experience with ad-tech identity concepts — cross-device identity, household graphs, cookie/ID deprecation, or media measurement.
  • Experience with graph databases or graph-processing frameworks (e.g., Neo4j, Neptune, GraphFrames, or similar).
  • Familiarity with our ML/data stack (Metaflow) or comparable large-scale data tooling.
  • Experience working with privacy-sensitive data and an understanding of relevant data governance and privacy considerations for identity data.
  • Experience applying GenAI to boost developer/analytics productivity.

Generally, our compensation structure consists solely of an annual salary; we do not have bonuses. You choose each year how much of your compensation you want in salary versus stock options. To determine your personal top of market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range. The range for this role is $330,000.00 - $566,000.00. This compensation range will vary based on location.Netflix provides comprehensive benefits including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits. We also offer paid leave of absence programs. Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off. Full-time salaried employees are immediately entitled to flexible time off. See more details about our Benefits here.
Netflix is a unique culture and environment. Learn more here.
Inclusionis a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner.
We are an equal-opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.
Job is open for no less than 7 days and will be removed when the position is filled.
Originally posted on Himalayas

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