Senior Data Analytics Engineer, YouTube
Google - Mountain View, CA
posted 5 months ago
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. These tools will guide business leadership in optimizing the efficiency of teams that interact with partners. The analytics team is responsible for managing YouTube's business data, which is essential for helping business leaders understand and make sense of operations through 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 while having fun together. This role will require you to conduct requirements gathering and project scoping sessions with subject matter experts, business users, and executive stakeholders to discover and define business data needs. You will also design, build, and optimize the data architecture and Extract, Transform, and Load (ETL) pipelines, making them accessible for Business Data Analysts, Data Scientists, and business users to enable data-driven decision-making. In addition, you will collaborate with analysts to productionalize and scale value-creating capabilities, including data integrations and transformations, model features, and statistical and machine learning models. You will drive standards in data reliability, integrity, and governance, ensuring that the data sets, business intelligence products, and analyses are accurate, consistent, and trustworthy. Engaging with the analyst community will be crucial, as you will need to communicate with analysts to understand user journeys and data sourcing inefficiencies, advocate for best practices, and lead training sessions for analysts.
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.
- 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
- Paid holidays
- Paid time off
- Parental leave
- Employee stock purchase plan
- Tuition reimbursement
- Professional development opportunities
