分析工程师 - 基础设施效率与生产力
Analytics Engineer - Infrastructure Efficiency & Productivity
在Netflix，我们的使命是娱乐全世界。我们正在书写下一章——突破叙事的边界、全球粉丝文化，并将难以想象的事情变为现实。我们是一支梦想团队，痴迷于探索创意、直觉和尖端技术融合时带来的不安与兴奋。加入我们，成为未来的一部分。
我们为会员打造的一切都依赖于我们庞大的技术基础设施，从我们在AWS上租用的服务到我们自主研发的内容分发网络，[Open Connect](https://media.netflix.com/en/company-blog/how-netflix-works-with-isps-around-the-globe-to-deliver-a-great-viewing-experience)。随着这一基础设施的增长，我们对AI工具的投资也在增加，理解我们如何高效利用这些资源是Netflix投资决策的核心。
作为平台数据科学与工程团队的高级分析工程师，你将负责Netflix如何理解其云和AI基础设施的效率。你将加入一个由分析工程师、数据工程师、可视化工程师和数据科学家组成的数据组织，他们与工程团队和管理层合作，定义指标、构建数据集并提供公司依赖的洞察，以明智地进行支出。你的工作将成为工程师和高管用来做出关于数十亿美元基础设施规模决策的可信真相来源。
这是一个范围广泛、高可见度的角色，有很多发挥空间。你将有机会从零开始开发指标，构建其背后的逻辑和流程，通过仪表板和分析讲述故事，并将所有内容转化为改变团队投资方式的建议。你还将参与解决行业中最具挑战性的问题之一：量化日益智能化和代理增强型劳动力的生产力影响，在这个问题上没有标准答案，也存在设定标准的巨大空间。
理想的候选人将在指标研究与开发、自主分析工程和数据叙事方面表现出色，并热衷于持续改进我们使用数据来提升Netflix基础设施的方式。
了解更多关于我们的团队，请阅读[这里](https://netflixtechblog.com/how-our-paths-brought-us-to-data-and-netflix-4eced44a6872)。
### 在这个职位中，你将：
- 定义并负责Netflix理解其计算、存储、网络等基础设施成本、使用情况和效率的核心指标
- 与跨职能团队合作，设计和实现数据模型，支持基础设施优化和成本管理
- 开发自动化报告和仪表板，帮助团队监控和分析关键性能指标
- 与工程和产品团队协作，推动数据驱动的决策，优化资源分配
- 推动数据治理和质量保障措施，确保数据的准确性和一致性
- 与领导层沟通，提供战略见解，支持基础设施投资决策
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.
Everything that we build to delight our members relies on our extensive technical infrastructure, which spans from services we rent from AWS to our custom-built content delivery network, [Open Connect](https://media.netflix.com/en/company-blog/how-netflix-works-with-isps-around-the-globe-to-deliver-a-great-viewing-experience). As that infrastructure grows, so does investment in AI tooling, and understanding how efficiently we use both is central to Netflix's investment decisions.
As a Senior Analytics Engineer on Platform Data Science & Engineering, you will own how Netflix understands the efficiency of its cloud and AI infrastructure. You will join a data org of Analytics Engineers, Data Engineers, Visualization Engineers, and Data Scientists who partner with engineering teams and leadership to define the metrics, build the datasets, and deliver the insights that the company relies on to spend wisely. Your work will be the trusted source of truth that engineers and executives use to make decisions about a multi-billion-dollar infrastructure footprint.
This is a broad, high-visibility role with a lot of white space. You'll have the opportunity to develop metrics from scratch, build the logic and pipelines behind them, tell the story through dashboards and analyses, and turn all of it into recommendations that change how teams invest. You'll also help pioneer one of the most salient problems in the industry: quantifying the productivity impact of an increasingly AI- and agent-augmented workforce, where there is no textbook answer and real room to set the standard.
The ideal candidate will excel in metric research and development, self-sufficient analytics engineering, and data storytelling, and will share a passion for continuously improving how we use data to enhance Netflix's infrastructure.
To learn more about our team, read [here](https://netflixtechblog.com/how-our-paths-brought-us-to-data-and-netflix-4eced44a6872).
### In this role, you will:
- Define and own the core metrics for how Netflix understands infrastructure cost, usage, and efficiency across its compute, storage, streaming, and machine learning platforms, and expand that coverage as the footprint grows.
- Help pioneer new ways to measure the productivity impact of AI tooling and autonomous agents, shaping frameworks that leadership across the company will use to guide investment.
- Increase the speed and quality with which the company understands and acts on its efficiency, turning what is often slow, manual analysis into trusted, reusable insight.
- Surface and size new efficiency opportunities, translating patterns in cost and usage data into recommendations that lead directly to meaningful savings.
- Tell the story with data: build the dashboards, reports, and narratives that make efficiency legible to audiences from individual engineers to senior executives, partnering with our visualization engineers on the surfaces that serve them.
- Partner with Data Engineers on the pipelines upstream of your metrics, and with Data Scientists on the forecasting and reliability work that connects to yours.
### You are:
- Experienced in metric research and development in a technical domain: you build metric frameworks (not just one-off metrics) at multiple granularities that ladder up to a coherent whole, and you set targets people trust.
- Self-sufficient across the full analytics loop: data exploration, cleaning, light pipeline building, business logic, and dashboards. Fluent in Python and SQL.
- At home in messy, changing data, with the judgment to know when a number is right and when it needs a second look.
- An exceptional communicator with both technical and non-technical audiences, experienced at telling stories with data and influencing decisions at all levels of the business.
- A strong product thinker with good product sense: you get at what your partners actually need and build solutions that satisfy it.
- Comfortable with ambiguity, and you thrive with minimal oversight and process.
- Thoughtful about using AI in your own craft, using coding and analytics agents well, and evaluating what they produce rather than taking it on faith.
- Experienced in measuring cost, efficiency, or system performance in a cloud or streaming context (a plus), or motivated to go deep in that domain.
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](https://jobs.netflix.com/work-life-philosophy).
Netflix is a unique culture and environment. Learn more [here](https://jobs.netflix.com/culture).
[Inclusion](https://about.netflix.com/en/inclusion) is 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.