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Netflix Software Engineer L4 - CKG United States, California, Los Angeles 960771813
12.07.2024
Who you are:
- You would consider yourself a full-stack developer. You have experience in both backend and frontend development for a good part of your career and expertise in owning and maintaining backend services.
- You are proficient in designing, building, and operating API layers that support various front-end user experiences. Experience with GraphQL and is a big plus.
- API and SDK development: You have built, maintained, evolved, and/or sunset a variety of APIs and libraries/SDKs.
- You are proficient in working with Javascript, React, or other similar technologies. Proficiency in Python or Java is a big plus.
- Comfortable with SQL and using big data technologies (e.g. Hive, Presto, Spark, Iceberg, etc) on medium to large-scale data.
- You are willing to learn and own all areas of the software lifecycle: design, development, test, deployment, operation, and support.
- Conceptually familiar or interested in learning graph technologies (e.g. databases, data models, query languages)
- You have strong communication skills and can collaborate with cross-functional team members and partners on projects that drive high-impact outcomes
- Excited about learning new business domains, demonstrating excellence, and growing your career
What you will do:
- Work cross-functionally to build new services, tools, and data models to develop easy-to-use data access patterns for knowledge graphs.
- Building intuitive user interfaces backed by data in offline systems and APIs
- Evaluate new technologies and approaches to streamline and improve our rapid application development tooling and conventions.
- Regularly learn new systems and tools as the Netflix platform and ecosystem evolve.
- Understand business requirements and provide tools that empower teams to innovate on top of the Netflix KG
- Join a stunning team with diverse skill sets (data engineering, machine learning, analytical engineering and software engineering), partnering closely with data science, analytics, and business counterparts
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