Senior Analytics Engineer
@ Netflix

Amsterdam, North Holland, Netherlands
€120,000
On Site
Full Time
Posted 11 hours ago

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Job Details

About Netflix

Netflix is one of the world's leading entertainment services, with over 300 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 anytime and anywhere.

Role Overview - Senior Analytics Engineer

In this role based in Amsterdam, you will design and develop analytic tools and systems to monitor the adoption and accountability of our algorithms for promotional media. You will partner with ML engineers, data scientists, product managers and creative stakeholders to shape the future of promotional asset recommendation and generation at Netflix.

Responsibilities

  • Act as a strategic partner with stakeholders to identify analytic opportunities.
  • Develop scalable analytic tools and high-visibility dashboards.
  • Collaborate closely with ML engineers and data scientists to enhance recommendation models.
  • Share innovations and strengthen analytics enablement within the community.
  • Serve as the go-to expert on Media AI Solutions Data Science and Engineering.

About You

You have 5+ years of experience building data products, strong proficiency in Python, SQL, Spark, and data visualization tools such as Plotly Dash and Tableau. You are well-versed in statistical inference, data engineering best practices, and have a proactive approach to managing ambiguity with minimal oversight. Bonus if you have experience with media file pipelines and visualizations.

Key Skills/Competency

  • Analytics
  • Python
  • SQL
  • Spark
  • Data Visualization
  • Statistical Inference
  • Big Data
  • Machine Learning
  • Dashboard Design
  • Scalability
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How to Get Hired at Netflix

🎯 Tips for Getting Hired

  • Customize your resume: Tailor your analytics experience for Netflix.
  • Highlight technical skills: Emphasize Python, SQL, Spark expertise.
  • Demonstrate collaboration: Showcase cross-functional project achievements.
  • Showcase data projects: Provide examples of scalable tool development.

📝 Interview Preparation Advice

Technical Preparation

Practice Python coding challenges.
Review SQL query optimization techniques.
Familiarize with Spark data pipelines.
Build interactive dashboards with visualization tools.

Behavioral Questions

Describe a time leading cross-functional projects.
Explain handling ambiguous project requirements.
Share how you manage stakeholder expectations.
Discuss a situation requiring innovative analytics solutions.

Frequently Asked Questions