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Netflix is one of the world's leading entertainment services, with 283 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 as much as they want, anytime, anywhere, and can change their plans at any time. Securing our members’ data appropriately is key to maintaining a high level of trust with our customers. In addition, securing our technology infrastructure and understanding inherent risks are essential to enable us to scale our business effectively while maintaining a healthy security posture. The Security Data Engineering team builds data products which provide visibility into security, fraud and technology risks across customer accounts as well as internal systems and data. This role is specifically focused on enabling our security teams in detecting and mitigating various types of security risks affecting our expansive cloud technology footprint. This requires a holistic understanding of our infrastructure topology, access controls, security policies and usage patterns. Centralizing various data points which help us understand these dimensions is key to success in this role. We are looking for a Data Engineer to build reliable data pipelines and intuitive data products that allow our stakeholders to easily leverage data in an effective manner. As part of this team, you will work on diverse data technologies such as Spark, Presto, Flink, Kafka and others to build insightful, scalable and robust data pipelines; write ETL jobs to collect and aggregate data; and build high quality data models that describe the entities, interactions and usage patterns of our technology footprint. The ideal candidate will bring a strong track record of having built data systems and frameworks to strengthen the security posture at large consumer businesses. They will have a deep background in distributed data processing and share our passion for continuously improving Netflix's security posture. This role is based in the contiguous US and our teams work in a hybrid-working model.
