Join the YouTube Business Strategy & Operations team, a vital part of the YouTube Business Organization, dedicated to driving go-to-market functions. This team shapes priorities to accelerate growth and strategically allocates resources. It blends deep strategic, operational, and problem-solving expertise with a pragmatic approach to executing change across a global organization.

You will contribute to a community of analytics professionals working on impactful projects. These range from developing critical data pipelines that support business operations to building tools that analyze content partnerships and the creator ecosystem. Your work will guide business leadership in optimizing the effectiveness and efficiency of partner-facing teams.

Leverage SQL and YouTube's Extract, Transform, Load (ETL) systems to generate insightful datasets. You will establish best practices for data sets and reporting, cultivating broad expertise across various data domains. At YouTube, we champion the power of voice and community through shared stories. We empower individuals to share their narratives, explore their passions, and connect with others, all while moving at the speed of culture.

Collaborate with analysts to productionize and scale valuable capabilities. This includes enhancing data integrations, transformations, model features, and statistical/machine learning models.

Develop and maintain robust data platforms that ensure data reliability, integrity, and governance, leading to accurate, consistent, and trustworthy data sets.

Lead requirements gathering and project scoping sessions with subject matter experts, business users, and executive stakeholders to precisely define business data needs.

Design, construct, and optimize the data architecture, along with extract, transform, and load (ETL) pipelines.

Author and review comprehensive end-user and technical documentation. This includes requirements and design documents for current and future data systems, as well as data standards and policies.

A Bachelor's degree or equivalent practical experience is required. You should possess at least 3 years of coding experience in one or more programming languages.

Demonstrate 3 years of experience in designing data pipelines and dimensional data modeling for both synchronous and asynchronous system integration. This should include implementation using internal stacks like Flume and external stacks such as DataFlow and Spark.

Possess 3 years of experience working with data infrastructure and data models, performing exploratory queries and scripts. A Master’s degree in a quantitative field like Computer Science, Engineering, Statistics, or Mathematics is preferred, along with experience in data warehouses, large-scale distributed data platforms, data lakes, AI, and Gen AI data applications.