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Data Engineer - Product - Streaming Data Engineering - Device at Netflix (Remote)

Work from home Full-time role Hiring

Join the Netflix Team as a Data Engineer - Product and Revolutionize Streaming Data Engineering

Are you a talented Data Engineer looking to make a significant impact in the world of streaming data engineering? Do you have a passion for building scalable data pipelines and delivering high-quality business datasets? Look no further! Netflix, the world's leading entertainment service, is seeking a skilled Data Engineer - Product to join our Streaming Data Engineering team. As a remote employee, you will have the opportunity to work with a talented team of engineers and contribute to the development of innovative data solutions that power our streaming services.

About Netflix and Our Culture

Netflix is a unique and dynamic company that values creativity, innovation, and teamwork. With 283 million paid memberships in over 190 countries, we are committed to providing an exceptional entertainment experience for our members. Our culture is built on the principles of freedom, responsibility, and inclusion, and we strive to create an environment where our employees can thrive and grow.

Our Team

The Device pod within the Streaming Data Engineering team is responsible for producing high-quality and large-scale datasets that serve as a source of truth for how Netflix services operate on various devices. We partner with multiple engineering teams to create datasets used to certify and retire devices, categorize them, and identify changes in this constantly changing environment. As a Data Engineer - Product, you will play a critical role in supporting Netflix's core data assets, delivering high-quality business datasets and metrics, and building systems to process batch and real-time data at a large scale.

Key Responsibilities

  • Design and Development: Engineer efficient, adaptable, and scalable data pipelines to process structured and unstructured data.
  • Data Quality and Excellence: Help Netflix support and evolve the device data model by improving data excellence and quality, supporting analytics, developing and maintaining metrics, and partnering with engineering to deliver the next generation of Netflix experiences.
  • Collaboration and Partnership: Partner with numerous engineering teams, analytics engineers, and data scientists to enhance playback-related datasets.
  • Pipelines Maintenance and Improvement: Maintain and rethink existing pipelines to improve scalability and maintainability.
  • Operational Excellence: Take ownership of the operational excellence in your domain, ensuring that data pipelines are running smoothly and efficiently.

Requirements and Qualifications

Essential Qualifications:

  • Programming Skills: Mastery over at least one major programming language (e.g., Java, Scala, Python) and comfortable working with SQL.
  • Big Data Technologies: Familiarity with big data technologies like Spark and Flink and comfortable working with web-scale datasets.
  • Distributed Data Processing: Strong background in distributed data processing or software engineering of data services.
  • Software Development: Passionate about the end-to-end software development lifecycle, focusing on automation, testing, CI/CD, and documentation.
  • DevOps and Operations: Practical, solid DevOps and Operation fundamentals, and enjoy total ownership of your domain.

Preferred Qualifications:

  • Device Lifecycle: Solid understanding of the device lifecycle.
  • Data Intuition: Eye for detail, good data intuition, and a passion for data quality.
  • Netflix Culture: Relate to and embody many of the aspects of the Netflix Culture, including a love for working independently while also collaborating and giving/receiving candid feedback.
  • Adaptability: Comfortable working in a rapidly changing environment with ambiguous requirements, and willing to take intelligent risks.

What We Offer

Compensation and Benefits:

We offer a competitive salary, with a range of $170,000 - $720,000, depending on experience and qualifications. Our compensation structure consists solely of an annual salary, and you choose each year how much of your compensation you want in salary versus stock options. We also provide comprehensive benefits, including:

  • Health Plans: Medical, dental, and vision coverage.
  • Mental Health Support: Access to mental health resources and support.
  • 401(k) Retirement Plan: With employer match.
  • Stock Option Program: Opportunity to own a part of the company.
  • Disability Programs: Disability insurance and family-forming benefits.
  • Health Savings and Flexible Spending Accounts: Options for saving and spending on healthcare expenses.
  • Paid Leave of Absence Programs: Flexible time off and paid leave for various life events.

Career Growth and Learning:

At Netflix, we are committed to helping our employees grow and develop their skills. As a Data Engineer - Product, you will have opportunities to:

  • Learn New Technologies: Stay up-to-date with the latest big data technologies and software development techniques.
  • Collaborate with Experts: Work with experienced engineers, data scientists, and analytics engineers.
  • Take Ownership: Have total ownership of your domain and make significant contributions to the company's data assets.

Work Environment and Culture:

As a remote employee, you will have the flexibility to work from anywhere and enjoy a healthy work-life balance. Our culture is built on the principles of freedom, responsibility, and inclusion, and we strive to create an environment where our employees can thrive and grow.

How to Apply

If you are a motivated and talented Data Engineer looking to make a significant impact in the world of streaming data engineering, we encourage you to apply for this exciting opportunity. Please submit your application, including your resume and a cover letter, and we will be in touch to discuss the next steps.

Don't hesitate to apply if you don't meet every single requirement. We value a great attitude and a willingness to learn above all. We look forward to hearing from you!

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