Infrastructure Partner Data Engineer

1 Month ago • 1 Years + • Data Analyst

Job Summary

Job Description

As an Infrastructure Partner Data Engineer at YouTube's Measurement Infrastructure Partner Engineering team, you'll manage infrastructure solutions powering strategic initiatives like public claims and Ads partner integrations. You'll design and implement data pipeline solutions using internal (Flume) and external stacks (DataFlow, Spark) to combine data from multiple sources. Responsibilities include managing YouTube data feeds, providing technical support to internal partners, guaranteeing technical aspects of data integrations, identifying and optimizing third-party reporting opportunities, and writing/maintaining code for ETL pipelines. You'll also incorporate Generative AI to improve scale and efficiency. The role requires expertise in data pipelines, dimensional data modeling, and programming languages like Python, C/C++, Java, or Go.
Must have:
  • Bachelor's degree or equivalent experience
  • 1+ year coding experience (Python, C/C++, Java, Go)
  • 1+ year experience designing data pipelines
  • Experience with data modeling and exploratory queries
  • Manage YouTube data feeds and provide technical support
Good to have:
  • Stakeholder management experience
  • Project planning and delivery experience
  • Experience with statistical methodology and BI tools (Tableau, Power BI, etc.)

Job Details

Minimum qualifications:

  • Bachelor's degree or equivalent practical experience.
  • 1 year of experience coding in one or more programming languages like Python, C/C++, Java, Go, Unix/Linux systems.
  • 1 year 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 (e.g., DataFlow, Spark, etc.).
  • Experience working with data models by performing exploratory queries and scripts.

Preferred qualifications:

  • Experience partnering with stakeholders (e.g., users, partners, customer), and managing stakeholders/customers.
  • Experience developing project plans and delivering projects on time within budget and scope.
  • Experience with statistical methodology and data consumption tools such as business intelligence tools, collabs, jupyter notebooks, Tableau, Power BI, DataStudio, and business intelligence platforms.

About the job

As an infrastructure partner data engineer on the YouTube Measurement Infrastructure Partner Engineering team, you will be responsible for managing infrastructure solutions that will power YouTube's various strategic initiatives such as public claims and Ads partner integrations.

In this role, you will have the opportunity to design and implement data pipeline solutions combining data from multiple internal and external data sources. You will also incorporate Generative AI into new and existing operations to drive scale and efficiency.

At YouTube, we believe that everyone deserves to have a voice, and that the world is a better place when we listen, 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 cutting-edge 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

  • Manage YouTube data feeds and provide ongoing technical support to internal partners for a wide range of YouTube’s viewership metrics initiatives.
  • Provide infrastructure solutions for both external audience measurement partner integrations and internal partner engineering teams.
  • Guarantee the technical aspects of YouTube viewership data integrations by providing technical guidance and documentation.
  • Identify, drive, and optimize new third-party reporting opportunities by leveraging YouTube technologies.
  • Write and maintain lines of code (e.g., Python, C++, etc.) to support Extract, Transform, Load (ETL) pipelines.

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