Netflix
Analytics Engineer 5 - New Content Experiences DSE
USA - Remote · Full-time
Sponsorship not specified$330k-$566kDetected 1 day ago
PythonAlgorithmsSQLSparkData AnalysisData EngineeringData ScienceProduct StrategyCommunicationCollaborationHadoop
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odds of building a lasting career here
37Unrated
Cap-exempt (no lottery)0
Sponsors this role0
Entry-level history0
PERM / green-card track0
Lottery odds (Level IV)94
Fits your clock70
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About the role
- The New Content Experiences team focuses on introducing new content types and innovative experiences to our product.
- The most recently launched example of a New Content Experience is our Live offering (including WWE and the NFL Christmas games among other great hits!).
Responsibilities
- Partner directly with our stakeholders (e.g., Data Scientists, Product Managers, Designers, Engineers) on data, metrics & analytics initiatives
- Lead end-to-end development of analysis and tools used by your direct stakeholders and a diverse set of teams across the company
- Collaborate with the data engineering and data science teams to ensure data quality, integrity, and availability for analysis
- Drive the direction and execution of your work, which spans from developing scrappy analysis and tools to designing scalable systems
Requirements
- 5+ years of experience in leveraging technical skills in manipulating large data sets with complex SQL and Python (or similar languages), big data technologies (e.g., Hadoop, Spark), and visualization tools
Skills
- Data Science and Engineering ('DSE') at Netflix is aimed at using data, analytics, and sciences to improve various aspects of our business.
Compensation
- $330k-$566k
Company info
- 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.
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This listing is sourced directly from Netflix's careers page and normalized into a canonical job model.