Data Engineer YouTube Business Organization

Minimum qualifications:

• Bachelors degree or equivalent practical experience.
• 3 years of experience coding in one or more programming languages.
  
• 3 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.).
  
• 3 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, Maths).
• Experience with data warehouses, large-scale distributed data platforms, data lakes, artificial intelligence and Gen AI data applications.
• Ability to break down complex, multi-dimensional problems along with structured thinking.
• Ability to navigate ambiguity and work in a fluid environment with multiple stakeholders.
• Excellent business and technical communication, organizational, and analytical skills.

About the job:

gTech’s Product and Tools Operations team (gPTO) leverages deep user, operational, and technical insights to innovate Googles 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.

With over 2 billion monthly logged-in users, YouTube has grown into a global community where people all over the world access information, share video, and shape culture. The YouTube team helps budding creators build careers, artists and Media Companies reach audiences, creates products like YouTube Kids, YouTube Music, and YouTube TV.

The YouTube Business Strategy & Operations team is responsible for driving all go-to-market functions for the YouTube Business Organization (Biz Org). The team is responsible for shaping go-to-market priorities to accelerate growth and resource the business accordingly. This team combines deep strategic, operational, and problem solving skills with a pragmatic sense of how to get things done and drive change across a global organization.

You will be part of a community of analytics professionals who work on impactful projects ranging from developing critical data pipelines that help run the business, build tools to analyze the content partnerships and creator ecosystem which guide business leadership on optimizing the effectiveness and efficiency of our partner facing business teams.

We use SQL and YouTube’s Extract, Transform, Load (ETL) systems to produce useful datasets, establish best practices for data sets and reporting, and develop a breadth of expertise in various data domains.

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:

• Work closely with analysts to productionize and scale value-creating capabilities, including data integrations and transformations, model features, and statistical and machine learning models.
• 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.
• 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.

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