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Google · google.com · checked today

Data Engineer, YouTube Business Organization

gTech’s Product and Tools Operations team (gPTO) leverages deep user, operational, and technical insights to innovate Google's Ads products into customer experiences that are so intuitive (or automated) that they require no support at all. gPTO partners closely with gTech’s Support, Professional Services, Product Management, and Engineering teams to innovate and simplify our Ads products and build the productivity tools ecosystem for gTech users. With over 2 billion monthly logged-in users, YouTube has grown into a global community where people all over the world access information, share vide

Skills, with evidence

• Data modelling
  3 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.).must havewrong?
• SQL
  We use SQL and YouTube’s 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.must havewrong?
• Spark
  3 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.).must havewrong?
• Data quality
  Build and maintain data platforms to enable data reliability, data integrity, and data governance, enabling accurate, consistent, and trustworthy data sets.must havewrong?
• AWS
  Experience with data warehouses, large-scale distributed data platforms, data lakes, artificial intelligence and Gen AI data applications.not practised herewrong?
• Streaming
  3 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.).wrong?
• Cost & performance
  Design, build, and optimize the data architecture and extract, transform, and load (ETL) pipelines.wrong?
• Governance & security
  Build and maintain data platforms to enable data reliability, data integrity, and data governance, enabling accurate, consistent, and trustworthy data sets.not practised herewrong?
• Machine learning
  Work closely with analysts to productionize and scale value-creating capabilities, including data integrations and transformations, model features, and statistical and machine learning models.not practised herewrong?