Analytics Engineer (L5) - Regional Understanding



Data Science
Los Gatos, CA, USA
Posted on Saturday, May 25, 2024
Netflix is one of the world's leading entertainment services, with 270 million paid memberships in over 190 countries, enjoying TV series, films, and games across a wide variety of genres and languages. Members can play, pause, and resume watching as much as they want, anytime, anywhere, and can change their plans at any time.
In this role, you will dive into different regions and countries to holistically answer questions like “Who are our members?”, “How satisfied are current members with our service?” and “How do the needs and expectations of non-members differ from those of members?” The questions you answer will help shape how senior leadership thinks about opportunities and challenges in these different regions, and enable us to evaluate and determine how our country-level strategies are performing.
As a Senior Analytics Engineer, you will be responsible for developing and maintaining data pipelines, conducting in-depth analyses, and developing tools and products to create a single source of truth around Netflix's greatest consumer-facing opportunities and challenges—at both a company and country level.
The ideal candidate will excel in data analytics, storytelling with data, cross-functional collaboration, clear communication with executive stakeholders, and share a passion for continuously improving the way we use data to make Netflix better.
To learn more about analytics engineering at Netflix, read here.

In this role, you will:

  • Become an expert in country-level performance by diving deep into our data to understand both our members and non-members.
  • Spearheaded research to understand the consumer-facing opportunities and challenges facing Netflix.
  • Scale these insights—Netflix is a global company, and we need to be able to efficiently zoom in on different regions throughout the world and ladder this up to a global view.
  • Share your learnings with high-level leaders in a way that is digestible, actionable, and clear.

To be successful in this role, you have:

  • At least 5 years of experience as an analytics professional.
  • Expertise in SQL, programming skills (e.g. Python, Scala), and some exposure to ETL and data warehousing concepts.
  • A proven track record of data analysis, reporting and visualization (e.g. Tableau, D3).
  • Strong communication with the ability to build meaningful stakeholder relationships.
  • Enthusiasm for creative thinking and innovation in a fast-paced data and analytics space.
  • Excitement to learn about new fields, with the ability to be scrappy as needed.
  • Comfort with ambiguity; able to thrive with minimal oversight and process.
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 $170,000 - $720,000.
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 detail about our Benefits here.
Netflix is a unique culture and environment. Learn more here.
We are an equal-opportunity employer and celebrate diversity, recognizing that diversity of thought and background 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.