Senior Data Analytics Engineer, YouTube

$146,000 - $216,000/Yr

YouTube - San Bruno, CA

Full-time - Mid Level

San Bruno, 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 that works on a variety of projects aimed at enhancing business operations through data-driven insights. Your primary responsibilities will include developing data pipelines that are crucial for running the business, as well as building tools that analyze the content partnerships and creator ecosystem. This analysis will guide business leadership in optimizing the efficiency of partner-facing business teams. The team plays a vital role in managing YouTube's business data, ensuring that business leaders can make informed decisions based on accurate business intelligence. At YouTube, we believe in the power of storytelling and community. Our mission is to empower everyone to share their stories, explore their passions, and connect with others. Working at the intersection of cutting-edge technology and creativity, we strive to move at the speed of culture, exploring new ideas and solving real problems collaboratively. We foster an environment where innovation thrives, and we have fun while doing it. As a Senior Data Analytics Engineer, you will contribute to this mission by leveraging your expertise in data architecture and analytics to drive impactful business outcomes. The role requires a strong foundation in designing data pipelines and dimensional data modeling for both synchronous and asynchronous system integration. You will be expected to work closely with various stakeholders, including subject matter experts and executive leadership, to gather requirements and define business data needs. Your work will involve designing, building, and optimizing data architectures and ETL pipelines, ensuring that they are accessible to Business Data Analysts, Data Scientists, and other business users. Additionally, you will be responsible for driving standards in data reliability, integrity, and governance, which are essential for maintaining accurate and trustworthy data sets and business intelligence products.

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 synchronous and asynchronous 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
• Dental insurance
• Vision insurance
• 401(k) plan with matching contributions
• Paid time off
• Parental leave
• Employee stock purchase plan
• Tuition reimbursement
• Professional development opportunities