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Google · google.com · checked today

Data Engineer, Data Architecture and Engineering, gTech Strategy and Operations

As a Data Engineer in gData, you’ll design and build the foundational data infrastructure that powers the GBO data needs. You’ll manage complex, large-scale issues using Google’s proprietary tech stack to deliver a highly reliable Single Source of Truth. In this role, you will have the opportunity to architect innovative data pipelines and solutions that directly enable predictive problem-solving and AI-driven business decisions at scale.Google creates products and services that make the world a better place, and gTech’s role is to help bring them to life.

Skills, with evidence

• Python
  Design, develop, test, and maintain reliable and scalable data pipelines and Extract, Transform, Load and Extract, Load, Transform (ETL/ELT) architectures using Google's distributed data systems (e.g., advanced SQL, Python).must havewrong?
• SQL
  Design, develop, test, and maintain reliable and scalable data pipelines and Extract, Transform, Load and Extract, Load, Transform (ETL/ELT) architectures using Google's distributed data systems (e.g., advanced SQL, Python).must havewrong?
• Data modelling
  Contribute to the modernization of the Google Ads Data Infrastructure (GDI) and Customer Data Platform (CDP), optimizing data models to ensure our Single Source of Truth remains robust and performant.must havewrong?
• Spark
  1 year of experience with data processing software (e.g., Hadoop, Spark, Pig, Hive) and algorithms (e.g., MapReduce, Flume).must havewrong?
• Data quality
  Advocate data quality by authoring clear technical design documents, executing code reviews, and proactively resolving complex bugs and support escalations.must havewrong?
• Java
  Experience with database administration techniques or data engineering, as well as writing software in Java, C++, Python, Go, or JavaScript.must have · not practised herewrong?
• Warehousing
  Experience in technical consulting and working with data warehouses, including data warehouse technical architectures, infrastructure components, ETL/ELT, and reporting/analytic tools and environments.wrong?
• Machine learning
  Experience working with Big Data, information retrieval, data mining, or machine learning.not practised herewrong?