Data powers Netflix. It permeates our thoughts, informs our decisions, and challenges our assumptions. It fuels experimentation
at unprecedented scale. It helps us discover fantastic content
and deliver personalized experiences for our 130 million members around the world.
Making this possible is no small feat; it requires extensive engineering and infrastructure support. Every day more than 1 trillion events are written into a streaming ingestion pipeline, which is processed and stored in a 100PB data warehouse. To support data at this scale, we’ve built an industry-leading, cloud-native data platform which is flexible, powerful, and complex (by necessity).
The Big Data Tools team is working to simplify this complexity. Our charter is to imagine, design, and craft tooling to make it easier for Netflix to do amazing things with data. And we need your help.
We’re seeking an experienced software engineer to work on Jupyter kernels for our notebook infrastructure. This role is a unique opportunity to have an outsized impact--both at Netflix and around the world.
Every day our users rely on notebooks to work with data, spanning everything from reporting and analysis to machine learning and recommendation algorithms. You will be responsible for providing high-quality Jupyter kernels for Scala, Spark, and R to support these use cases. Your work will focus heavily on improving kernel stability, reliability, and visibility for our users. And because we’re working with open-source projects, your work will likely be used in data science, machine learning, and AI projects around the world.
We understand that sometimes the best engineers are not the ones who ‘check all the boxes’. If you answer “yes” to a majority of the skills & traits below--and you’re enthusiastic about the role and motivated to learn and grow--then we’d love to talk with you!
Who are you?
- You are an experienced software engineer who takes pride in the code you write. You’re constantly honing your craft, and you value clean, elegant, and efficient code.
- You thrive in a culture of freedom and self-direction, and you understand the responsibility that comes with autonomy.
- You enjoy collaborating with others. You value diversity of thought and embrace feedback from your stunning colleagues.
- You are biased toward action. You deliver results quickly with iteration, instead of waiting for perfection, and you actively solicit feedback.
- You are intensely curious. You’re always learning something new or digging deeper to understand how something works.
- You have a passion for quality and keen attention to detail. You don’t consider work done until it has been tested and documented.
What do you know?
- You have significant experience delivering high-quality backend software with minimal technical guidance.
- You are highly skilled with Scala; you understand good design principles and stay current on best practices.
- You have hands-on experience with Jupyter kernel development, or strong knowledge of the underlying fundamentals such as sockets, messaging protocols, and interpreters.
- You have proficiency with scripting languages like Python and R.
- You possess a positive attitude, willingness to learn, and desire to grow.
Bonus if you’re familiar with:
- contributing to open source projects
- notebook technologies - Jupyter, Zeppelin, IPython, ObservableHQ, etc.
- big data technologies - Apache Spark, Flink, Hadoop, etc.
- containerized cloud-based environments - AWS, Google, Azure, Docker, etc.
- analytics lifecycle - exploratory analysis, data engineering, ad hoc queries, reporting, deployment
- data science concepts - machine learning, R, stat packages (e.g. pandas, NumPy), feature engineering, predictions, model training and evaluation
Netflix's culture is a huge part of what makes us successful. We are an equal opportunity employer; we celebrate diversity and are intentional about inclusion, recognizing that diversity of thought and background builds stronger teams. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.