As an Analytics Engineer within YouTube Analytics and Decision Support, you will be part of a community of analytics professionals who work on impactful projects. In this role, you will develop critical data pipelines that help run the business, and build tools to analyze the content partnerships and creator ecosystem that guides business leadership. You will build data sets, pipe data in and out of our tools, and make it useful for analysts across the organization to drive reporting and insights.
At YouTube, we believe that everyone deserves to have a voice, and that the world is a better place when we listen, share, and build community through our stories. We work together to give everyone the power to share their story, explore what they love, and connect with one another in the process. Working at the intersection of cutting-edge technology and boundless creativity, we move at the speed of culture with a shared goal to show people the world. We explore new ideas, solve real problems, and have fun - and we do it all together.
• Oversee requirements to gather and scope project sessions with subject matter experts, business users, and executive stakeholders to discover and define business data needs.
• Design, build, and optimize the data architecture and Extract, Transform, and Load (ETL) pipelines to make them accessible for Business Data Analysts, Data Scientists, and business users to enable data-driven decision-making.
• Work with Analysts to productionize and scale value-creating capabilities, including data integrations, transformations, model features, and statistical and machine learning models.
• Drive the highest standards in data reliability, data integrity, and data governance, enabling accurate, consistent, trustworthy data sets, business intelligence products, and analyses.
• Write and review end-user and technical documents, including requirements and design documents for existing and future data systems, as well as data standards and policies.
• Bachelor's degree in Economics, Engineering, Computer Science, Mathematics, Physics, Statistics, Finance, or equivalent practical experience.
• 5 years of experience with data warehouses and distributed data platforms.
• 3 years of experience using SQL.
• 3 years of experience in programming (i.e., Python, C++, Java).
• Master's degree in a quantitative discipline (e.g., Computer Science, Engineering, Statistics, or Math).
• Experience with data warehouses, large-scale distributed data platforms, and data lakes.
• Ability to break down complex multi-dimensional problems.
• Ability to navigate ambiguity in a fast-paced environment with multiple stakeholders.
• Excellent business and technical communication, organizational, and analytical skills.
Jobcode: Reference SBJ-gp07yo-44-192-94-86-42 in your application.