Senior Data Engineer, YouTube
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Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 5 years of experience in designing data pipelines, and dimensional data modeling for synch and asynch system integration and implementation using internal (e.g., Flume, etc.) and external stacks (e.g., DataFlow, Spark, etc.).
- 5 years of experience with coding in one or more programming languages.
- 5 years of experience in working with data infrastructure and data models by performing exploratory queries and scripts.
Preferred qualifications:
- Master’s degree in Computer Science, Engineering, Statistics, Math, or a related quantitative field.
- Experience with data warehouses and maintaining distributed data platforms, and data lakes.
- Ability to break down multi-dimensional problems.
- Ability to navigate ambiguity and work in a changing environment with multiple stakeholders.
- Excellent business and technical communication, organizational, and investigative skills.
About the job
In this role, you will be part of a community of analytics professionals who work on projects ranging from building and maintaining data platforms, developing data pipelines that help run the business, build tools to analyze the content partnerships and creator ecosystem. You will be responsible for democratizing YouTube’s business data, helping business leaders make sense of business operations through accurate business intelligence.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.Responsibilities
- Build and maintain data platforms to enable data reliability, data integrity, and data governance, enabling accurate and consistent data sets. Design, build, and optimize the data architecture and extract, transform, and load (ETL) pipelines.
- Conduct requirements gathering and project scoping sessions with subject matter experts, business users, and executive stakeholders to discover and define business data needs.
- Work with analysts to productionize capabilities, including data integrations and transformations, model features, and statistical and machine learning models.
- 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.
- Engage with the analyst community, communicate with analysts to understand user journeys and data sourcing inefficiencies, advocate best practices and lead analyst trainings.
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