Data Engineer (L5) - Security

6 Months ago • 5-7 Years • Data Analyst • $100,000 PA - $720,000 PA

Job Summary

Job Description

Netflix is seeking a Data Engineer to build reliable data pipelines and intuitive data products for security and fraud mitigation. Strong experience with big data technologies, SQL, and fraud/security domain knowledge is required.
Must have:
  • Data Pipeline Engineering
  • Big Data Technologies
  • SQL Proficiency
  • Security/Fraud Domain
Good to have:
  • Java/Python/Scala
  • ETL Development
  • Data Modeling
  • Cross-Functional Collaboration
Perks:
  • Stock Options
  • Flexible Time Off

Job Details

Netflix is one of the world’s leading entertainment services with 278 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.

The Role

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 Data Engineering team builds data products which provide visibility into security and fraud 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 fraud like account takeovers, unauthorized third party apps, account sharing fraud 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 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. 

Who you are:

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

  • Highly proficient in at least one of Java, Python or Scala with at least 7 years of software/data engineering experience

  • Advanced level SQL skills in a complex data environment

  • At least 5 years of experience in engineering data pipelines using big data technologies (Hive, Presto, Spark, Flink) 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 and fraud space is strongly preferre

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 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 . 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. 

Our compensation structure consists solely of an annual salary; we do not have bonuses. You choose each year how much of your compensation you want in salary versus stock options. To determine your personal top of market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range. The range for this role is $100,000 - $720,000. Netflix provides comprehensive benefits including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits. We also offer paid leave of absence programs.  Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off. Full-time salaried employees are immediately entitled to flexible time off.

We are an equal-opportunity employer and celebrate diversity, recognizing that diversity of thought and background builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.

Job is open for no less than 7 days and will be removed when the position is filled.

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About The Company

Netflix is one of the world's leading entertainment services with over 247 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.

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