Netflix Data Engineer L5 - Security 

Poland, Masovian Voivodeship, Warsaw 

881063746

A comprehensive understanding of our infrastructure topology, access controls, security policies, and usage patterns is essential. Centralizing diverse data points to enhance our understanding of these dimensions is vital for 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.

• Passionate about building intuitive data products to understand and mitigate security risks

• Highly proficient in at least one of Java, Python or Scala (Scala preferred) with at least 6 years of data engineering experience

• Advanced level SQL skills in a complex data environment

• At least 4 years of experience in engineering data pipelines using big data technologies (Spark, Presto, Flink etc.) on medium to large scale data sets

• Comfortable working cross functionally with multiple types of stakeholders groups

• Able to successfully lead large, complex systems design and implementation challenges independently

• Prior experience in the security space is strongly preferred

• 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 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 ofwith diverse skill sets, partnering closely with analytics engineering and data science counterparts

A few more things to know:

. We regularly share examples of our work on our. 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.