Data Engineer, YouTube

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

gTech’s Product and Tools Operations team (gPTO) leverages deep user, operational, and technical insights to innovate Google's Ads products into customer experiences that are so intuitive (or automated) that they require no support at all. gPTO partners closely with gTech’s Support, Professional Services, Product Management, and Engineering teams to innovate and simplify our Ads products and build the productivity tools ecosystem for gTech users.

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, 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.