About Netflix At Netflix, our mission is to entertain the world. With over 200 million paid members in over 190 countries on hundreds of thousands of devices, we're revolutionizing how entertainment is produced, consumed, and experienced. We're pushing the boundaries of technology to deliver streaming video at a massive scale over the internet, and constantly improving the end-to-end consumer experience with Netflix across their member journey. About the Role We're seeking an experienced Part-Time Data Engineer to join our Data Science team at Netflix. As a Data Engineer, you'll be responsible for building structures to process data correctly and modeling the data to power analytics. You'll work on a wide range of projects, from batch data pipelines that bring business metrics to life to real-time processing services that integrate with our core product functions. Key Responsibilities Design, develop, and maintain large-scale data processing systems to support business analytics and decision-making Collaborate with cross-functional teams, including business, engineering, and data technology groups, to enable a culture of learning and knowledge-sharing Develop and maintain data pipelines, data warehouses, and data lakes to support data-driven decision-making Work with large datasets, including data from various sources, to build and maintain data models and analytics Develop and maintain data quality and data governance processes to ensure data accuracy and integrity Stay up-to-date with industry trends and emerging technologies to recommend and implement new solutions and tools Requirements To be successful in this role, you'll need to have a strong background in data engineering, including Essential Qualifications At least 3 years of experience in data engineering, with a focus on large-scale data processing and analytics Strong programming skills in languages such as Java, Scala, or Python, with experience working with big data technologies such as Hadoop, Spark, or Flink Experience working with data warehouses, data lakes, and data pipelines, including data modeling, data integration, and data quality Strong understanding of data governance and data quality principles, including data validation, data cleansing, and data transformation Experience working with cloud-based technologies, including AWS or GCP Strong communication and collaboration skills, with experience working with cross-functional teams Preferred Qualifications Master's degree in Computer Science, Data Science, or related field Experience working with machine learning and artificial intelligence technologies Experience working with data visualization tools, such as Tableau or Power BI Experience working with cloud-based data platforms, such as AWS Lake Formation or GCP BigQuery Experience working with containerization technologies, such as Docker Skills and Competencies To be successful in this role, you'll need to have a strong set of skills and competencies, including Technical Skills Programming languages Java, Scala, Python Big data technologies Hadoop, Spark, Flink Data warehouses AWS Redshift, GCP BigQuery Data lakes AWS S3, GCP Cloud Storage Cloud-based technologies AWS, GCP Containerization technologies Docker Soft Skills Strong communication and collaboration skills Strong problem-solving and analytical skills Strong attention to detail and organizational skills Ability to work in a fast-paced environment with multiple priorities Ability to adapt to changing requirements and priorities Career Growth Opportunities and Learning Benefits At Netflix, we're committed to helping our employees grow and develop their careers. As a Data Engineer, you'll have opportunities to work on a wide range of projects and technologies, and to develop your skills and expertise in areas such as data engineering, machine learning, and data science. We also offer a range of learning and development programs, including training and mentorship opportunities, to help you achieve your career goals. Work Environment and Company Culture At Netflix, we're committed to creating a work environment that's inclusive, diverse, and supportive. We believe that our employees are our greatest asset, and we're dedicated to providing them with the resources and support they need to succeed. Our company culture is built on a set of core values, including innovation, collaboration, and customer obsession. We're a fast-paced and dynamic company, and we're always looking for talented and motivated individuals to join our team. Compensation, Perks, and Benefits We offer a competitive salary and benefits package, including health insurance, retirement savings, and paid time off. We also offer a range of perks and benefits, including a generous stock option plan, on-site fitness classes, and access to a range of employee discounts and perks. How to Apply If you're a motivated and talented individual with a passion for data engineering and analytics, we'd love to hear from you. Please submit your resume and a cover letter explaining why you're the perfect fit for this role. We can't wait to hear from you! Interview Process Our interview process typically includes a series of technical and behavioral interviews, as well as a presentation or coding challenge. We're looking for individuals who are passionate about data engineering and analytics, and who have a strong set of technical and soft skills. We're also looking for individuals who are a good fit for our company culture and values. Common Interview Questions Here are some common interview questions that we ask in this role Technical Questions What is your experience with data engineering and analytics? Can you explain the difference between a data warehouse and a data lake? How do you handle data quality and data governance in a large-scale data processing system? Can you explain the concept of data modeling and how it applies to data engineering? How do you optimize data processing and analytics for large-scale datasets? Behavioral Questions Can you tell me about a time when you had to troubleshoot a complex technical issue? How do you handle conflicting priorities and deadlines in a fast-paced environment? Can you describe a project you worked on that involved data engineering and analytics? How do you communicate technical information to non-technical stakeholders? Can you tell me about a time when you had to adapt to a new technology or tool? Conclusion We're excited to hear from you and learn more about your qualifications and experience. Thank you for considering this opportunity to join our team at Netflix. We look forward to hearing from you soon!