Analytics Engineer 5 - Infrastructure Efficiency & Productivity
在 Netflix,我们的使命是娱乐世界。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,痴迷于发现你融合创造力,直觉和尖端技术时会发生什么事物的不舒服兴奋。来做接下来的的一部分。我们为我们的成员提供了各种服务,从我们租来的服务到自定义的内容交付网络 (Open Connect) [https://media.netflix.com/en/company-blog/how-netflix-works-with-isps-around-the-glob-to-deliver-a-great-viewing-experience).随着该基础设施的增长,对人工智能工具的投资也会增加,以及我们如何有效地使用这两者都很重要。作为 Netflix 平台数据科学与工程高级分析工程师,你将拥有 Netflix 了解其云和人工智能基础设施的效率的方式。你将加入一个数据组织,包括分析工程师,数据工程师,可视化工程师和数据科学家,他们与工程团队和领导层合作定义指标,构建数据集并提供公司依赖于智能度地花费的见解。你的工作将是工程师和高管使用的真相来源来做出数十亿美元基础设施足迹决定。这是一个广泛的,具有大量白色空间的高度可见性的角色。你将有机会从零开始开发测量,构建其背后的逻辑和管道,通过仪表板和分析讲述故事,并把所有这些转化为改变团队投资方式的建议。你还将帮助先行业中最突出的问题之一:量化人工智能和代理增强员工人数的影响,没有教科书答案和真正的空间来设定标准。理想候选人在测量研究和发展,自给自足的分析工程和数据叙事方面取得了卓越成绩,并且分享我们不断改善如何使用数据来提高 Netflix 基础设施的热情。为了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). ### 在这个角色中,你将:-定义和拥有 Netflix 如何理解基础设施成本,使用和效率的核心指标
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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.