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Open nowFirst seen 5 hours ago

Data Engineer, YouTube India

Google3,357 open roles

Where
Bengaluru, Karnataka, India
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Your applicationOpen nowData Engineer, YouTube IndiaGoogle · Bengaluru, Karnataka, India

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on Google's own form.

The reply lands in your private mailbox

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The clock on this job

Early applications get read.

8.2% of postings close within 7 days. Measured by our own scanner across the market. Google postings stay open a median of 26 days.

Share of postings closed within
  1. 1.9%1 day
  2. 3.8%3 days
  3. 8.2%7 days
  4. 15.2%14 days
  5. 34.1%30 days
This job: first seen 5 hours ago

Google median: 26 days open

The posting

In most instances, this position requires in-person interviews as part of the hiring process

Minimum qualifications:

  • Bachelor's degree in Computer Science, Mathematics, a related field, or equivalent practical experience.
  • 5 years of experience with data warehouses, distributed data platforms, and data lakes.
  • Experience writing software in Java, C++, Python, Go, or JavaScript.
  • Experience in stakeholder management.

Preferred qualifications:

  • Experience working with data warehouses, including data warehouse technical architectures, infrastructure components, ETL/ELT, and reporting/analytic tools and environments.
  • Experience working with Big Data, information retrieval, data mining, or machine learning.
  • Experience in building multi-tier high availability applications with modern web technologies (e.g., NoSQL, MongoDB, SparkML, TensorFlow).
  • Ability to navigate ambiguity and excel in a fast paced environment with multiple stakeholders.

About the job

Data is the fundamental building block for every tool and every insight. We build the data products 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. We are responsible for democratizing YouTube’s business data, helping business leaders make sense of business operations through timely, accurate, and robust business intelligence. We build and maintain the YouTube Extract, Transform, Load (ETL) systems to produce useful datasets, establish best practices for data sets and reporting, and develop a breadth of expertise in various data domains. Ultimately, data engineers scale centralized reporting, to ensure the business is operating more effectively and efficiently.

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 ranging from building and maintaining data platforms, developing critical data products that help run the business, build tools to analyze the content partnerships and creator ecosystem which guide business leadership on optimizing the effectiveness and efficiency of our partner facing business teams.

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

  • Conduct requirements gathering and project scoping sessions with subject matter experts, business users, and executive stakeholders to discover and define business data needs.
  • Code, work with APIs, build front-end products to automate and simplify processes.
  • Build and maintain data platforms to enable data reliability, data integrity, and data governance, enabling accurate, consistent, and trustworthy data sets.
  • 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.
  • Engage with the analyst community, communicate with analysts to understand critical user journeys and data sourcing inefficiencies, advocate best practices and lead analyst trainings.
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