Data Engineer, YouTube Business Technology
Description For Data Engineer, YouTube Business Technology
Join YouTube's Business Technology team as a Data Engineer where you'll play a crucial role in developing and maintaining solutions that streamline data access, enhance data hygiene, and improve telemetry for YouTube's internal business teams. As part of YouTube/Video Global Solutions, you'll be instrumental in keeping YouTube and Video free and accessible worldwide by translating market needs into product solutions. You'll work with cutting-edge technologies including cloud platforms like GCP, Looker, and potentially generative AI models. The role combines technical expertise in data engineering with business impact, requiring skills in pipeline development, advanced analytics, and data governance. You'll collaborate with cross-functional teams, lead technical designs, and establish data visualization standards. This position offers the opportunity to work at Google, a company known for its innovative culture and global impact, with comprehensive benefits and a commitment to diversity and inclusion. The role requires both technical depth in data engineering and the ability to partner effectively with stakeholders to drive business outcomes.
Responsibilities For Data Engineer, YouTube Business Technology
- Lead the design, development, and maintenance of reliable data pipeline
- Write queries and other data manipulation languages like Python and R. Conduct advanced quantitative data analysis
- Partner with technical and non-technical stakeholders to translate data needs into technical designs
- Develop dashboards and reports in partnership with User Experience (UX) team
- Drive ownership of the Data Governance charter, defining and implementing policies and ensuring compliance
Requirements For Data Engineer, YouTube Business Technology
- Bachelor's degree or equivalent practical experience
- 3 years of experience coding in one or more programming languages
- 3 years of experience working with data infrastructure and data models
- Experience in data analysis, database querying (SQL), and data visualization
- Experience in defining and implementing data governance policies and standards
