Senior Data Engineer, YouTube Data Science

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.

The YouTube Data Science team influences and informs YouTube’s product and engineering leadership to improve decisions with science. In this role, you will take initiative to develop projects and collaborate horizontally across YouTube, working with feature teams and stakeholders.

The US base salary range for this full-time position is $156,000-$226,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Responsibilities

• Design and build data processing systems (pipelines, feature stores, and automation) with a particular emphasis on security, compliance, scalability, efficiency, reliability, and portability.
  
• Create or consult in creating data visualizations using Business Intelligence (BI) tools (e.g., Business Intelligence Platform, Datastudio, Tableau, etc.) and Gemini. 
  
• Develop and maintain data models, pipelines, and exchange formats to assist in the visualization, analysis, and interpretation of data and for use of data in ML training/models. 
  
• Provide ongoing support for data users through maintenance of reports, queries, and dashboards, fielding user questions, authoring documentation, and delivering training.
  
• Partner across engineering, product, and data science teams to ensure the timely launch of new analyses, features, and metrics.

Qualifications

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:

• 5 years of experience with statistical methodology and data consumption tools such as business intelligence tools, collabs, jupyter notebooks, Tableau, Power BI, DataStudio, and business intelligence platforms.
• 3 years of experience developing project plans and delivering projects on time within budget and scope.
  
• 3 years of experience partnering with stakeholders (e.g., users, partners, customer), and managing stakeholders/customers.
  
• Experience with Machine Learning for production workflows.