What You Will Do
The Title and Launch Management Analytics Engineering team helps to deliver high-quality, high-impact data products and insights for our Studio business, spanning areas like content launch planning, production, post-production, and marketing. We operate at the intersection of analytics and data engineering, enabling our data scientist and business users to make data-informed decisions. As an Analytics Engineer, you will be a key contributor to this mission, building and scaling data pipelines and tools that enable deep analytical insights into our business. You will partner with stakeholders across the organization, including data scientists, business leaders, and engineering teams, to understand their needs and deliver innovative solutions.
You will have an opportunity to:
- Partner with data scientists and business stakeholders to understand their analytical needs and translate them into robust, scalable data products.
- Design, develop, and maintain high-quality data pipelines, ETLs, and data models using SQL, Python, and other relevant tools.
- Build and maintain data warehousing solutions, ensuring data quality, reliability, and accessibility.
- Collaborate with engineering teams to integrate data solutions into broader Netflix systems.
- Develop and implement data governance best practices, ensuring data accuracy, privacy, and security.
- Drive innovation by exploring new technologies and methodologies in the data analytics space.
- Mentor junior team members and contribute to a culture of continuous learning and improvement.
- Act as a subject matter expert for data in your domain, providing guidance and support to data consumers.
Who You Are
We are looking for an experienced Analytics Engineer with a passion for data, a strong analytical mindset, and a proven track record of building and scaling data products. You should be comfortable working independently, collaborating with cross-functional teams, and thriving in a fast-paced, dynamic environment.
Key Qualifications:
- 5+ years of experience in data engineering, analytics engineering, or a related field.
- Strong proficiency in SQL and Python, with experience in data warehousing concepts (e.g., Snowflake, Databricks, Redshift).
- Experience with ETL/ELT development, data modeling, and schema design.
- Familiarity with cloud platforms (e.g., AWS, GCP, Azure) and distributed computing technologies (e.g., Spark, Hadoop).
- Excellent communication, collaboration, and problem-solving skills.
- Ability to translate complex business requirements into technical solutions.
- Experience with data visualization tools (e.g., Tableau, Looker) is a plus.
- Experience working in the entertainment industry or with content-related data is a plus.
- Experience with Airflow or similar workflow orchestration tools is a plus.
