Data Engineer, YouTube
Google · Bengaluru, Karnataka, India
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- On site
- Full-time
- $150,000 / year
- Bengaluru, Karnataka, India
Job highlights
- Build and maintain YouTube's data platforms.
- Design, build, and optimize ETL pipelines.
- Work with analysts on data integrations.
- Gather requirements from stakeholders.
- Ensure data reliability and governance.
About the role
Data Engineer, YouTube
The YouTube team helps budding creators build careers, artists and media companies reach audiences, and create products like YouTube Kids, YouTube Music, and YouTube TV. The YouTube Business Strategy and Operations team is responsible for driving all go-to-market functions for the YouTube business organization.
As a Data Engineer within YouTube Analytics and Data Science, you will be part of a community of analytics professionals who work on impactful projects. You will build the data sets that help run the business, piping the relevant data into and out of our tools, and making it useful for analysts across the organization to drive reporting and insights. You will be responsible for democratizing YouTube’s business data, helping business leaders make sense of business operations through timely, accurate, and business intelligence. You will build and maintain the YouTube 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 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 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
- 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.
- Work closely with analysts to productionize and scale value-creating capabilities, including data integrations and transformations, model features, and statistical and machine learning models.
- Engage with the analyst community, understand critical user journeys and data sourcing inefficiencies, advocate best practices and lead analyst trainings.
- 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.
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
- Master’s degree in a quantitative discipline (e.g., Computer Science, Engineering, Statistics, Math).
- Experience with data warehouses, large-scale distributed data platforms, and data lakes.
- Ability to navigate ambiguity in a fast-paced environment with multiple stakeholders.
- Excellent structured thinking skills, with the ability to break down complex, multi-dimensional problems.
- Excellent business and technical communication, organizational, and problem-solving skills.
Key skills/competency
- Data Engineering
- Data Pipelines
- ETL
- Data Modeling
- Data Warehousing
- Spark
- Data Science
- Big Data
- Python
- SQL
Skills & topics
- Data Engineer
- YouTube
- Data Pipelines
- ETL
- Data Modeling
- Data Warehousing
- Spark
- Data Science
- Big Data
- Python
- SQL
- Cloud Data Engineering
- Analytics
How to get hired
- Tailor your resume: Highlight your 5+ years of experience in data pipeline design, dimensional data modeling, and coding. Quantify achievements with data.
- Showcase relevant skills: Emphasize experience with internal/external stacks like Flume, DataFlow, and Spark, plus data warehouses and data lakes.
- Prepare for technical interviews: Be ready to discuss data infrastructure, model design, ETL processes, and write exploratory queries and scripts.
- Demonstrate problem-solving: Articulate your ability to navigate ambiguity, break down complex problems, and communicate technical concepts clearly.
- Research Google's values: Understand Google's commitment to equal opportunity and affirmative action. Align your application with their mission and culture.
Technical preparation
Behavioral questions
Frequently asked questions
- What are the key responsibilities for a Data Engineer at YouTube?
- As a Data Engineer on the YouTube Analytics and Data Science team, your key responsibilities include building and maintaining data platforms, designing and optimizing ETL pipelines, and working with analysts to productionize data capabilities. You'll also gather business data needs and ensure data reliability and governance.
- What technical skills are most important for this Data Engineer role at Google?
- The most important technical skills for this role include 5+ years of experience in designing data pipelines, dimensional data modeling, and coding. Proficiency with internal and external data stacks like Flume, DataFlow, and Spark, as well as experience with data warehouses, distributed data platforms, and data lakes, are highly valued.
- What is the educational background preferred for a Data Engineer at YouTube?
- While a Bachelor's degree or equivalent practical experience is the minimum requirement, a Master’s degree in a quantitative discipline such as Computer Science, Engineering, Statistics, or Math is preferred for this Data Engineer position.
- How does Google approach diversity and inclusion for its Data Engineer roles?
- Google is proud to be an equal opportunity workplace and an affirmative action employer. They are committed to equal employment opportunity regardless of race, color, religion, sex, national origin, sexual orientation, disability, or gender identity. Qualified applicants are considered regardless of criminal histories.
- What kind of problems will a Data Engineer solve at YouTube?
- A Data Engineer at YouTube will solve problems related to democratizing business data, making it useful for analysts to drive reporting and insights. This involves building and maintaining ETL systems, ensuring data reliability and integrity, and helping business leaders understand operations through accurate business intelligence.
- Is experience with specific programming languages required for the YouTube Data Engineer role?
- Yes, the minimum qualifications require 5 years of experience coding in one or more programming languages. While specific languages aren't listed, common languages for data engineering like Python, Java, or Scala are typically expected.