Data Engineer (L4) - Security

Netflix is enjoyed by more than 200 million members globally, entertaining new audiences every day.  Securing our members data and accounts appropriately is key to maintaining a high level of trust with our customers. In addition, securing our service and guarding against fraudulent behavior is essential to enable us to scale our business effectively.  
The Security and Platform Data Engineering team builds data products which enable architecting secure, reliable, scalable, and efficient platforms. We partner with our security and platform engineering teams to empower them with data for smarter decision making and innovative solutions to challenging problems. 
This role is specifically focused on enabling our security teams in detecting and mitigating various types of fraud like account takeovers, unauthorized third party apps, ripping content etc. This requires a holistic understanding of members' activity patterns across various dimensions like geography, device types, content types and more. 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 the Netflix product. 
The ideal candidate will have a strong background in distributed data processing, have great and demonstrable data intuition, and share our passion for continuously improving the ways we use data to make the Netflix infrastructure better. 

Who you are:

• Passionate about building intuitive data products 
• Highly proficient in at least one of Java, Python or Scala with at least 2 years of software/data engineering experience
• Comfortable with advanced SQL
• Experienced in engineering data pipelines using big data technologies (Hive, Presto, Spark, Flink) on medium to large scale data sets
• Conceptually familiar or interested in learning security technology concepts and techniques
• Excel at taking requirements and implementing scalable data models and pipelines 
• Excited about demonstrating excellence, learning new technologies and growing your career 

What you will do:

• Engineer efficient, adaptable and scalable data pipelines to process structured and unstructured data 
• Develop a deep understanding of the security ecosystem at Netflix 
• Partner with the security engineering teams to understand product goals and provide data which empowers teams to improve our fraud and security posture 
• Maintain and rethink existing datasets and pipelines
• Enable smart analytics by building robust, reliable, and useful data sets that can power various analytic techniques like regression, classification, clustering etc
• Join a stunning team of data engineers with diverse skill sets, partnering closely with analytics engineering and data science counterparts

A few more things to know: 
Our culture is unique and we live by our values, so it's worth learning more about Netflix at jobs.netflix.com/culture. We regularly share examples of our work on our tech blog. You will need to be comfortable working in the most agile of environments. Requirements will be vague. Iterations will be rapid. You will need to be nimble and take smart risks.
At Netflix, we carefully consider a wide range of compensation factors to determine your personal top of market. We rely on market indicators to determine compensation and consider your specific job, skills, and experience to get it right. These considerations can cause your compensation to vary and will also be dependent on your location. 
The overall market range for roles in this area of Netflix is typically $150,000 - $750,000. 
This market range is based on total compensation (vs. only base salary), which is in line with our compensation philosophy. Netflix is a unique culture and environment. Learn more here.