Senior Data Analytics Engineer, YouTube

$146,000 - $216,000/Yr

YouTube - Mountain View, CA

Full-time - Mid Level

Mountain View, CA

Broadcasting and Content Providers

About the position

As a Senior Data Analytics Engineer within YouTube and Decision Support, you will be part of an analytics team responsible for developing data pipelines and tools that analyze content partnerships and the creator ecosystem. This role is crucial for guiding business leadership in optimizing the efficiency of partner-facing business teams and ensuring accurate business intelligence for YouTube's operations.

Responsibilities

• 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 to make them accessible for Business Data Analysts, Data Scientists, and business users to enable data-driven decision-making.
• Work with analysts to productionalize and scale value-creating capabilities including data integrations and transformations, model features, and statistical and machine learning models.
• Drive standards in data reliability, data integrity, and data governance, enabling accurate, consistent, and trustworthy data sets, business intelligence products, and analyses.
• Engage with the analyst community, communicate with analysts to understand user journeys and data sourcing inefficiencies, advocate best practices, and lead analyst training.

Requirements

• 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 and external stacks.
• 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.

Nice-to-haves

• Master's degree in a quantitative field (e.g., Computer Science, Engineering, Statistics, Math).
• Experience with data warehouses, distributed data platforms, and data lakes.
• Ability to navigate ambiguity and work in a fast-moving environment with multiple stakeholders.
• Ability to break down multi-dimensional problems.
• Excellent business and technical communication, organizational, and problem-solving skills.

Benefits

• Health insurance
• 401k
• Paid holidays
• Flexible scheduling
• Professional development opportunities