Netflix - Los Angeles, CA
posted about 2 months ago
The Device pod within the Streaming Data Engineering team at Netflix is dedicated to partnering with multiple engineering teams to produce high-quality, large-scale datasets that serve as a source of truth for the operation of Netflix services across a diverse range of devices. This team plays a crucial role in creating datasets that are essential for certifying and retiring devices, categorizing them, and identifying changes in the ever-evolving landscape of device technology. The primary focus of this role is to support Netflix's core data assets by delivering high-quality business datasets and metrics, as well as building systems capable of processing both batch and real-time data at a large scale. Candidates for this position should possess a deep understanding of large distributed systems, modern big data technologies, and software development techniques. At Netflix, data engineers are responsible for their own data pipelines, which necessitates a strong sense of ownership regarding operational excellence within their domain. The ideal candidate will demonstrate excellent data intuition and a passion for continuously improving the handling of streaming data at Netflix. In this role, you will be expected to write elegant code and independently learn new technologies. Mastery over at least one major programming language (such as Java, Scala, or Python) and proficiency in SQL are essential. You will collaborate with teams to push the boundaries of analytical insights, create new product features using data, and power machine-learning models. A strong background in distributed data processing or software engineering of data services is required, along with familiarity with big data technologies like Spark and Flink. You should also be comfortable working with web-scale datasets and have a passion for the end-to-end software development lifecycle, emphasizing automation, testing, CI/CD, and documentation. At Netflix, you will own your code, services, and pipelines, demonstrating solid DevOps and operational fundamentals while enjoying total ownership of your domain. A solid understanding of the device lifecycle, attention to detail, good data intuition, and a commitment to data quality are also important attributes for success in this role.