Data Engineer, YouTube
Job Description
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 5 years of experience designing data pipelines, and dimensional data modeling for synch and asynch system integration and implementation using internal (e.g., Flume, etc.) and external stacks (DataFlow, Spark, etc.).
- 5 years of experience coding in one or more programming languages.
- 5 years of experience working with data infrastructure and data models by performing exploratory queries and scripts.
Preferred qualifications:
- Master’s degree in a quantitative discipline (e.g., Computer Science, Engineering, Statistics, Math).
- Experience with data warehouses, large-scale distributed data platforms, and data lakes.
- Ability to navigate ambiguity in a fast-paced environment with multiple stakeholders.
- Excellent structured thinking skills, with the ability to break down complex, multi-dimensional problems.
- Excellent business and technical communication, organizational, and problem-solving skills.
About the job
The YouTube team helps budding creators build careers, artists and media companies reach audiences, and create products like YouTube Kids, YouTube Music, and YouTube TV. The YouTube Business Strategy and Operations team is responsible for driving all go-to-market functions for the YouTube business organization.
At YouTube, we believe that everyone deserves to have a voice, and that the world is a better place when we 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 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, consistent, and trustworthy data sets.
- Conduct requirements gathering and project scoping 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.
- Work closely with analysts to productionize and scale value-creating capabilities, including data integrations and transformations, model features, and statistical and machine learning models. Engage with the analyst community, understand critical user journeys and data sourcing inefficiencies, advocate best practices and lead analyst trainings.
- 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.
About us
Google’s mission is to organize the world‘s information and make it universally accessible and useful.
Since our founding in 1998, Google has grown by leaps and bounds. From offering search in a single language we now offer dozens of products and services—including various forms of advertising and web applications for all kinds of tasks—in scores of languages. And starting from two computer science students in a university dorm room, we now have thousands of employees and offices around the world. A lot has changed since the first Google search engine appeared. But some things haven’t changed: our dedication to our users and our belief in the possibilities of the Internet itself.